Problem when Converting a Fine-tuned Checkpoint from TF to PyTorch using ALBERTxxlargev1 Model
# 🐛 Bug

## Information

Model I am using : ALBERTxxlargeV1

Language I am using the model on : English

The problem arises when using: Converting fine-tuned checkpoint from TF to PyTorch. No Problem with converting pre-trained checkpoints from TF.
* [ ] the official example scripts: 
```
!python /content/transformers/src/transformers/convert_albert_original_tf_checkpoint_to_pytorch.py \
--tf_checkpoint_path /content/pretrained_models/albertsquad/model.ckpt-best \
--albert_config_file /content/pretrained_models/albertsquad/config.json \
--pytorch_dump_path /content/pretrained_models/albertsquad/pytorch_model.bin
```
My vocabulary model was also placed on the same folder with the name "spiece.model" along with model.ckpt-best.index and model.ckpt-best.meta

I think the problem resides here
https://github.com/huggingface/transformers/blob/352d5472b0c1dec0f420d606d16747d851b4bda8/src/transformers/modeling_albert.py#L120
and here
https://github.com/huggingface/transformers/blob/352d5472b0c1dec0f420d606d16747d851b4bda8/src/transformers/modeling_albert.py#L160
or to replace names in the structure of TF in lines around 70 in modeling_albert.py
The tasks I am working on is:
* [ ] an official GLUE/SQUaD task: SQUAD
* [ ] my own task or dataset: not related

## To reproduce

Steps to reproduce the behavior:

1. Pre-train ALBERTxx large model using v1 configuration on TF and then fine-tune it on GLUE or SQUAD Task using TF, not PyTorch. 
2. Copy TF checkpoint on a folder along with the sentence piece model as "spiece.model" and config file as "config.json"
3. Try to convert TF checkpoint to PyTorch and you will have this message

```
2020-04-13 21:26:33.470832: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
Building PyTorch model from configuration: AlbertConfig {
  "_num_labels": 2,
  "architectures": null,
  "attention_probs_dropout_prob": 0,
  "bad_words_ids": null,
  "bos_token_id": 2,
  "classifier_dropout_prob": 0.1,
  "decoder_start_token_id": null,
  "do_sample": false,
  "down_scale_factor": 1,
  "early_stopping": false,
  "embedding_size": 128,
  "eos_token_id": 3,
  "finetuning_task": null,
  "gap_size": 0,
  "hidden_act": "gelu",
  "hidden_dropout_prob": 0,
  "hidden_size": 4096,
  "id2label": {
    "0": "LABEL_0",
    "1": "LABEL_1"
  },
  "initializer_range": 0.01,
  "inner_group_num": 1,
  "intermediate_size": 16384,
  "is_decoder": false,
  "is_encoder_decoder": false,
  "label2id": {
    "LABEL_0": 0,
    "LABEL_1": 1
  },
  "layer_norm_eps": 1e-12,
  "layers_to_keep": [],
  "length_penalty": 1.0,
  "max_length": 20,
  "max_position_embeddings": 512,
  "min_length": 0,
  "model_type": "albert",
  "net_structure_type": 0,
  "no_repeat_ngram_size": 0,
  "num_attention_heads": 64,
  "num_beams": 1,
  "num_hidden_groups": 1,
  "num_hidden_layers": 12,
  "num_memory_blocks": 0,
  "num_return_sequences": 1,
  "output_attentions": false,
  "output_hidden_states": false,
  "output_past": true,
  "pad_token_id": 0,
  "prefix": null,
  "pruned_heads": {},
  "repetition_penalty": 1.0,
  "task_specific_params": null,
  "temperature": 1.0,
  "top_k": 50,
  "top_p": 1.0,
  "torchscript": false,
  "type_vocab_size": 2,
  "use_bfloat16": false,
  "vocab_size": 30000,
  "xla_device": null
}

INFO:transformers.modeling_albert:Converting TensorFlow checkpoint from /content/pretrained_models/albertCOVIDglue/model.ckpt-best
INFO:transformers.modeling_albert:Loading TF weight bert/embeddings/LayerNorm/beta with shape [128]
INFO:transformers.modeling_albert:Loading TF weight bert/embeddings/LayerNorm/beta/adam_m with shape [128]
INFO:transformers.modeling_albert:Loading TF weight bert/embeddings/LayerNorm/beta/adam_v with shape [128]
INFO:transformers.modeling_albert:Loading TF weight bert/embeddings/LayerNorm/gamma with shape [128]
INFO:transformers.modeling_albert:Loading TF weight bert/embeddings/LayerNorm/gamma/adam_m with shape [128]
INFO:transformers.modeling_albert:Loading TF weight bert/embeddings/LayerNorm/gamma/adam_v with shape [128]
INFO:transformers.modeling_albert:Loading TF weight bert/embeddings/position_embeddings with shape [512, 128]
INFO:transformers.modeling_albert:Loading TF weight bert/embeddings/position_embeddings/adam_m with shape [512, 128]
INFO:transformers.modeling_albert:Loading TF weight bert/embeddings/position_embeddings/adam_v with shape [512, 128]
INFO:transformers.modeling_albert:Loading TF weight bert/embeddings/token_type_embeddings with shape [2, 128]
INFO:transformers.modeling_albert:Loading TF weight bert/embeddings/token_type_embeddings/adam_m with shape [2, 128]
INFO:transformers.modeling_albert:Loading TF weight bert/embeddings/token_type_embeddings/adam_v with shape [2, 128]
INFO:transformers.modeling_albert:Loading TF weight bert/embeddings/word_embeddings with shape [30000, 128]
INFO:transformers.modeling_albert:Loading TF weight bert/embeddings/word_embeddings/adam_m with shape [30000, 128]
INFO:transformers.modeling_albert:Loading TF weight bert/embeddings/word_embeddings/adam_v with shape [30000, 128]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/embedding_hidden_mapping_in/bias with shape [4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/embedding_hidden_mapping_in/bias/adam_m with shape [4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/embedding_hidden_mapping_in/bias/adam_v with shape [4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/embedding_hidden_mapping_in/kernel with shape [128, 4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/embedding_hidden_mapping_in/kernel/adam_m with shape [128, 4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/embedding_hidden_mapping_in/kernel/adam_v with shape [128, 4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/LayerNorm/beta with shape [4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/LayerNorm/beta/adam_m with shape [4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/LayerNorm/beta/adam_v with shape [4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/LayerNorm/gamma with shape [4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/LayerNorm/gamma/adam_m with shape [4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/LayerNorm/gamma/adam_v with shape [4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/LayerNorm_1/beta with shape [4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/LayerNorm_1/beta/adam_m with shape [4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/LayerNorm_1/beta/adam_v with shape [4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/LayerNorm_1/gamma with shape [4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/LayerNorm_1/gamma/adam_m with shape [4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/LayerNorm_1/gamma/adam_v with shape [4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/attention_1/output/dense/bias with shape [4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/attention_1/output/dense/bias/adam_m with shape [4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/attention_1/output/dense/bias/adam_v with shape [4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/attention_1/output/dense/kernel with shape [4096, 4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/attention_1/output/dense/kernel/adam_m with shape [4096, 4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/attention_1/output/dense/kernel/adam_v with shape [4096, 4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/attention_1/self/key/bias with shape [4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/attention_1/self/key/bias/adam_m with shape [4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/attention_1/self/key/bias/adam_v with shape [4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/attention_1/self/key/kernel with shape [4096, 4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/attention_1/self/key/kernel/adam_m with shape [4096, 4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/attention_1/self/key/kernel/adam_v with shape [4096, 4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/attention_1/self/query/bias with shape [4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/attention_1/self/query/bias/adam_m with shape [4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/attention_1/self/query/bias/adam_v with shape [4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/attention_1/self/query/kernel with shape [4096, 4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/attention_1/self/query/kernel/adam_m with shape [4096, 4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/attention_1/self/query/kernel/adam_v with shape [4096, 4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/attention_1/self/value/bias with shape [4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/attention_1/self/value/bias/adam_m with shape [4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/attention_1/self/value/bias/adam_v with shape [4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/attention_1/self/value/kernel with shape [4096, 4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/attention_1/self/value/kernel/adam_m with shape [4096, 4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/attention_1/self/value/kernel/adam_v with shape [4096, 4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/dense/bias with shape [16384]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/dense/bias/adam_m with shape [16384]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/dense/bias/adam_v with shape [16384]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/dense/kernel with shape [4096, 16384]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/dense/kernel/adam_m with shape [4096, 16384]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/dense/kernel/adam_v with shape [4096, 16384]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/output/dense/bias with shape [4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/output/dense/bias/adam_m with shape [4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/output/dense/bias/adam_v with shape [4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/output/dense/kernel with shape [16384, 4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/output/dense/kernel/adam_m with shape [16384, 4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/output/dense/kernel/adam_v with shape [16384, 4096]
INFO:transformers.modeling_albert:Loading TF weight bert/pooler/dense/bias with shape [4096]
INFO:transformers.modeling_albert:Loading TF weight bert/pooler/dense/bias/adam_m with shape [4096]
INFO:transformers.modeling_albert:Loading TF weight bert/pooler/dense/bias/adam_v with shape [4096]
INFO:transformers.modeling_albert:Loading TF weight bert/pooler/dense/kernel with shape [4096, 4096]
INFO:transformers.modeling_albert:Loading TF weight bert/pooler/dense/kernel/adam_m with shape [4096, 4096]
INFO:transformers.modeling_albert:Loading TF weight bert/pooler/dense/kernel/adam_v with shape [4096, 4096]
INFO:transformers.modeling_albert:Loading TF weight global_step with shape []
INFO:transformers.modeling_albert:Loading TF weight output_bias with shape [3]
INFO:transformers.modeling_albert:Loading TF weight output_bias/adam_m with shape [3]
INFO:transformers.modeling_albert:Loading TF weight output_bias/adam_v with shape [3]
INFO:transformers.modeling_albert:Loading TF weight output_weights with shape [3, 4096]
INFO:transformers.modeling_albert:Loading TF weight output_weights/adam_m with shape [3, 4096]
INFO:transformers.modeling_albert:Loading TF weight output_weights/adam_v with shape [3, 4096]
bert/embeddings/LayerNorm/beta
bert/embeddings/LayerNorm/beta/adam_m
bert/embeddings/LayerNorm/beta/adam_v
bert/embeddings/LayerNorm/gamma
bert/embeddings/LayerNorm/gamma/adam_m
bert/embeddings/LayerNorm/gamma/adam_v
bert/embeddings/position_embeddings
bert/embeddings/position_embeddings/adam_m
bert/embeddings/position_embeddings/adam_v
bert/embeddings/token_type_embeddings
bert/embeddings/token_type_embeddings/adam_m
bert/embeddings/token_type_embeddings/adam_v
bert/embeddings/word_embeddings
bert/embeddings/word_embeddings/adam_m
bert/embeddings/word_embeddings/adam_v
bert/encoder/embedding_hidden_mapping_in/bias
bert/encoder/embedding_hidden_mapping_in/bias/adam_m
bert/encoder/embedding_hidden_mapping_in/bias/adam_v
bert/encoder/embedding_hidden_mapping_in/kernel
bert/encoder/embedding_hidden_mapping_in/kernel/adam_m
bert/encoder/embedding_hidden_mapping_in/kernel/adam_v
bert/encoder/transformer/group_0/inner_group_0/LayerNorm/beta
bert/encoder/transformer/group_0/inner_group_0/LayerNorm/beta/adam_m
bert/encoder/transformer/group_0/inner_group_0/LayerNorm/beta/adam_v
bert/encoder/transformer/group_0/inner_group_0/LayerNorm/gamma
bert/encoder/transformer/group_0/inner_group_0/LayerNorm/gamma/adam_m
bert/encoder/transformer/group_0/inner_group_0/LayerNorm/gamma/adam_v
bert/encoder/transformer/group_0/inner_group_0/LayerNorm_1/beta
bert/encoder/transformer/group_0/inner_group_0/LayerNorm_1/beta/adam_m
bert/encoder/transformer/group_0/inner_group_0/LayerNorm_1/beta/adam_v
bert/encoder/transformer/group_0/inner_group_0/LayerNorm_1/gamma
bert/encoder/transformer/group_0/inner_group_0/LayerNorm_1/gamma/adam_m
bert/encoder/transformer/group_0/inner_group_0/LayerNorm_1/gamma/adam_v
bert/encoder/transformer/group_0/inner_group_0/attention_1/output/dense/bias
bert/encoder/transformer/group_0/inner_group_0/attention_1/output/dense/bias/adam_m
bert/encoder/transformer/group_0/inner_group_0/attention_1/output/dense/bias/adam_v
bert/encoder/transformer/group_0/inner_group_0/attention_1/output/dense/kernel
bert/encoder/transformer/group_0/inner_group_0/attention_1/output/dense/kernel/adam_m
bert/encoder/transformer/group_0/inner_group_0/attention_1/output/dense/kernel/adam_v
bert/encoder/transformer/group_0/inner_group_0/attention_1/self/key/bias
bert/encoder/transformer/group_0/inner_group_0/attention_1/self/key/bias/adam_m
bert/encoder/transformer/group_0/inner_group_0/attention_1/self/key/bias/adam_v
bert/encoder/transformer/group_0/inner_group_0/attention_1/self/key/kernel
bert/encoder/transformer/group_0/inner_group_0/attention_1/self/key/kernel/adam_m
bert/encoder/transformer/group_0/inner_group_0/attention_1/self/key/kernel/adam_v
bert/encoder/transformer/group_0/inner_group_0/attention_1/self/query/bias
bert/encoder/transformer/group_0/inner_group_0/attention_1/self/query/bias/adam_m
bert/encoder/transformer/group_0/inner_group_0/attention_1/self/query/bias/adam_v
bert/encoder/transformer/group_0/inner_group_0/attention_1/self/query/kernel
bert/encoder/transformer/group_0/inner_group_0/attention_1/self/query/kernel/adam_m
bert/encoder/transformer/group_0/inner_group_0/attention_1/self/query/kernel/adam_v
bert/encoder/transformer/group_0/inner_group_0/attention_1/self/value/bias
bert/encoder/transformer/group_0/inner_group_0/attention_1/self/value/bias/adam_m
bert/encoder/transformer/group_0/inner_group_0/attention_1/self/value/bias/adam_v
bert/encoder/transformer/group_0/inner_group_0/attention_1/self/value/kernel
bert/encoder/transformer/group_0/inner_group_0/attention_1/self/value/kernel/adam_m
bert/encoder/transformer/group_0/inner_group_0/attention_1/self/value/kernel/adam_v
bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/dense/bias
bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/dense/bias/adam_m
bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/dense/bias/adam_v
bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/dense/kernel
bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/dense/kernel/adam_m
bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/dense/kernel/adam_v
bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/output/dense/bias
bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/output/dense/bias/adam_m
bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/output/dense/bias/adam_v
bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/output/dense/kernel
bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/output/dense/kernel/adam_m
bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/output/dense/kernel/adam_v
bert/pooler/dense/bias
bert/pooler/dense/bias/adam_m
bert/pooler/dense/bias/adam_v
bert/pooler/dense/kernel
bert/pooler/dense/kernel/adam_m
bert/pooler/dense/kernel/adam_v
global_step
output_bias
output_bias/adam_m
output_bias/adam_v
output_weights
output_weights/adam_m
output_weights/adam_v
Initialize PyTorch weight ['albert', 'embeddings', 'LayerNorm', 'beta'] from bert/embeddings/LayerNorm/beta
INFO:transformers.modeling_albert:Skipping albert/embeddings/LayerNorm/beta/adam_m
INFO:transformers.modeling_albert:Skipping albert/embeddings/LayerNorm/beta/adam_v
Initialize PyTorch weight ['albert', 'embeddings', 'LayerNorm', 'gamma'] from bert/embeddings/LayerNorm/gamma
INFO:transformers.modeling_albert:Skipping albert/embeddings/LayerNorm/gamma/adam_m
INFO:transformers.modeling_albert:Skipping albert/embeddings/LayerNorm/gamma/adam_v
Initialize PyTorch weight ['albert', 'embeddings', 'position_embeddings'] from bert/embeddings/position_embeddings
INFO:transformers.modeling_albert:Skipping albert/embeddings/position_embeddings/adam_m
INFO:transformers.modeling_albert:Skipping albert/embeddings/position_embeddings/adam_v
Initialize PyTorch weight ['albert', 'embeddings', 'token_type_embeddings'] from bert/embeddings/token_type_embeddings
INFO:transformers.modeling_albert:Skipping albert/embeddings/token_type_embeddings/adam_m
INFO:transformers.modeling_albert:Skipping albert/embeddings/token_type_embeddings/adam_v
Initialize PyTorch weight ['albert', 'embeddings', 'word_embeddings'] from bert/embeddings/word_embeddings
INFO:transformers.modeling_albert:Skipping albert/embeddings/word_embeddings/adam_m
INFO:transformers.modeling_albert:Skipping albert/embeddings/word_embeddings/adam_v
Initialize PyTorch weight ['albert', 'encoder', 'embedding_hidden_mapping_in', 'bias'] from bert/encoder/embedding_hidden_mapping_in/bias
INFO:transformers.modeling_albert:Skipping albert/encoder/embedding_hidden_mapping_in/bias/adam_m
INFO:transformers.modeling_albert:Skipping albert/encoder/embedding_hidden_mapping_in/bias/adam_v
Initialize PyTorch weight ['albert', 'encoder', 'embedding_hidden_mapping_in', 'kernel'] from bert/encoder/embedding_hidden_mapping_in/kernel
INFO:transformers.modeling_albert:Skipping albert/encoder/embedding_hidden_mapping_in/kernel/adam_m
INFO:transformers.modeling_albert:Skipping albert/encoder/embedding_hidden_mapping_in/kernel/adam_v
Initialize PyTorch weight ['albert', 'encoder', 'albert_layer_groups', '0', 'albert_layers', '0', 'attention', 'LayerNorm', 'beta'] from bert/encoder/transformer/group_0/inner_group_0/LayerNorm/beta
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/LayerNorm/beta/adam_m
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/LayerNorm/beta/adam_v
Initialize PyTorch weight ['albert', 'encoder', 'albert_layer_groups', '0', 'albert_layers', '0', 'attention', 'LayerNorm', 'gamma'] from bert/encoder/transformer/group_0/inner_group_0/LayerNorm/gamma
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/LayerNorm/gamma/adam_m
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/LayerNorm/gamma/adam_v
Initialize PyTorch weight ['albert', 'encoder', 'albert_layer_groups', '0', 'albert_layers', '0', 'full_layer_layer_norm', 'beta'] from bert/encoder/transformer/group_0/inner_group_0/LayerNorm_1/beta
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/full_layer_layer_norm/beta/adam_m
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/full_layer_layer_norm/beta/adam_v
Initialize PyTorch weight ['albert', 'encoder', 'albert_layer_groups', '0', 'albert_layers', '0', 'full_layer_layer_norm', 'gamma'] from bert/encoder/transformer/group_0/inner_group_0/LayerNorm_1/gamma
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/full_layer_layer_norm/gamma/adam_m
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/full_layer_layer_norm/gamma/adam_v
Initialize PyTorch weight ['albert', 'encoder', 'albert_layer_groups', '0', 'albert_layers', '0', 'attention', 'dense', 'bias'] from bert/encoder/transformer/group_0/inner_group_0/attention_1/output/dense/bias
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/dense/bias/adam_m
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/dense/bias/adam_v
Initialize PyTorch weight ['albert', 'encoder', 'albert_layer_groups', '0', 'albert_layers', '0', 'attention', 'dense', 'kernel'] from bert/encoder/transformer/group_0/inner_group_0/attention_1/output/dense/kernel
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/dense/kernel/adam_m
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/dense/kernel/adam_v
Initialize PyTorch weight ['albert', 'encoder', 'albert_layer_groups', '0', 'albert_layers', '0', 'attention', 'key', 'bias'] from bert/encoder/transformer/group_0/inner_group_0/attention_1/self/key/bias
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/key/bias/adam_m
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/key/bias/adam_v
Initialize PyTorch weight ['albert', 'encoder', 'albert_layer_groups', '0', 'albert_layers', '0', 'attention', 'key', 'kernel'] from bert/encoder/transformer/group_0/inner_group_0/attention_1/self/key/kernel
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/key/kernel/adam_m
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/key/kernel/adam_v
Initialize PyTorch weight ['albert', 'encoder', 'albert_layer_groups', '0', 'albert_layers', '0', 'attention', 'query', 'bias'] from bert/encoder/transformer/group_0/inner_group_0/attention_1/self/query/bias
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/query/bias/adam_m
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/query/bias/adam_v
Initialize PyTorch weight ['albert', 'encoder', 'albert_layer_groups', '0', 'albert_layers', '0', 'attention', 'query', 'kernel'] from bert/encoder/transformer/group_0/inner_group_0/attention_1/self/query/kernel
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/query/kernel/adam_m
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/query/kernel/adam_v
Initialize PyTorch weight ['albert', 'encoder', 'albert_layer_groups', '0', 'albert_layers', '0', 'attention', 'value', 'bias'] from bert/encoder/transformer/group_0/inner_group_0/attention_1/self/value/bias
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/value/bias/adam_m
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/value/bias/adam_v
Initialize PyTorch weight ['albert', 'encoder', 'albert_layer_groups', '0', 'albert_layers', '0', 'attention', 'value', 'kernel'] from bert/encoder/transformer/group_0/inner_group_0/attention_1/self/value/kernel
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/value/kernel/adam_m
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/value/kernel/adam_v
Initialize PyTorch weight ['albert', 'encoder', 'albert_layer_groups', '0', 'albert_layers', '0', 'ffn', 'bias'] from bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/dense/bias
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/ffn/bias/adam_m
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/ffn/bias/adam_v
Initialize PyTorch weight ['albert', 'encoder', 'albert_layer_groups', '0', 'albert_layers', '0', 'ffn', 'kernel'] from bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/dense/kernel
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/ffn/kernel/adam_m
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/ffn/kernel/adam_v
Initialize PyTorch weight ['albert', 'encoder', 'albert_layer_groups', '0', 'albert_layers', '0', 'ffn_output', 'bias'] from bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/output/dense/bias
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/ffn_output/bias/adam_m
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/ffn_output/bias/adam_v
Initialize PyTorch weight ['albert', 'encoder', 'albert_layer_groups', '0', 'albert_layers', '0', 'ffn_output', 'kernel'] from bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/output/dense/kernel
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/ffn_output/kernel/adam_m
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/ffn_output/kernel/adam_v
Initialize PyTorch weight ['albert', 'pooler', 'bias'] from bert/pooler/dense/bias
INFO:transformers.modeling_albert:Skipping albert/pooler/bias/adam_m
INFO:transformers.modeling_albert:Skipping albert/pooler/bias/adam_v
Initialize PyTorch weight ['albert', 'pooler', 'kernel'] from bert/pooler/dense/kernel
INFO:transformers.modeling_albert:Skipping albert/pooler/kernel/adam_m
INFO:transformers.modeling_albert:Skipping albert/pooler/kernel/adam_v
INFO:transformers.modeling_albert:Skipping global_step
INFO:transformers.modeling_albert:Skipping classifier/output_bias
Traceback (most recent call last):
  File "/content/transformers/src/transformers/convert_albert_original_tf_checkpoint_to_pytorch.py", line 61, in <module>
    convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.albert_config_file, args.pytorch_dump_path)
  File "/content/transformers/src/transformers/convert_albert_original_tf_checkpoint_to_pytorch.py", line 36, in convert_tf_checkpoint_to_pytorch
    load_tf_weights_in_albert(model, config, tf_checkpoint_path)
  File "/content/drive/My Drive/transformers/src/transformers/modeling_albert.py", line 140, in load_tf_weights_in_albert
    pointer = getattr(pointer, "bias")
  File "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py", line 576, in __getattr__
    type(self).__name__, name))
AttributeError: 'AlbertForMaskedLM' object has no attribute 'bias'
```
I totally understand since I am using a fine-tuned model I should use use AlbertForSequenceClassification class or AlbertForQuestionAnswering instead of AlbertForMaskedLM which actually I tried and nothing changed. below is the message error that I got : 
``` 
2020-04-13 21:29:01.166679: I tensorflow/stream_executor/platform/default/dso_loader.cc:44] Successfully opened dynamic library libcudart.so.10.1
Building PyTorch model from configuration: AlbertConfig {
  "_num_labels": 2,
  "architectures": null,
  "attention_probs_dropout_prob": 0,
  "bad_words_ids": null,
  "bos_token_id": 2,
  "classifier_dropout_prob": 0.1,
  "decoder_start_token_id": null,
  "do_sample": false,
  "down_scale_factor": 1,
  "early_stopping": false,
  "embedding_size": 128,
  "eos_token_id": 3,
  "finetuning_task": null,
  "gap_size": 0,
  "hidden_act": "gelu",
  "hidden_dropout_prob": 0,
  "hidden_size": 4096,
  "id2label": {
    "0": "LABEL_0",
    "1": "LABEL_1"
  },
  "initializer_range": 0.01,
  "inner_group_num": 1,
  "intermediate_size": 16384,
  "is_decoder": false,
  "is_encoder_decoder": false,
  "label2id": {
    "LABEL_0": 0,
    "LABEL_1": 1
  },
  "layer_norm_eps": 1e-12,
  "layers_to_keep": [],
  "length_penalty": 1.0,
  "max_length": 20,
  "max_position_embeddings": 512,
  "min_length": 0,
  "model_type": "albert",
  "net_structure_type": 0,
  "no_repeat_ngram_size": 0,
  "num_attention_heads": 64,
  "num_beams": 1,
  "num_hidden_groups": 1,
  "num_hidden_layers": 12,
  "num_memory_blocks": 0,
  "num_return_sequences": 1,
  "output_attentions": false,
  "output_hidden_states": false,
  "output_past": true,
  "pad_token_id": 0,
  "prefix": null,
  "pruned_heads": {},
  "repetition_penalty": 1.0,
  "task_specific_params": null,
  "temperature": 1.0,
  "top_k": 50,
  "top_p": 1.0,
  "torchscript": false,
  "type_vocab_size": 2,
  "use_bfloat16": false,
  "vocab_size": 30000,
  "xla_device": null
}

INFO:transformers.modeling_albert:Converting TensorFlow checkpoint from /content/pretrained_models/albertCOVIDglue/model.ckpt-best
INFO:transformers.modeling_albert:Loading TF weight bert/embeddings/LayerNorm/beta with shape [128]
INFO:transformers.modeling_albert:Loading TF weight bert/embeddings/LayerNorm/beta/adam_m with shape [128]
INFO:transformers.modeling_albert:Loading TF weight bert/embeddings/LayerNorm/beta/adam_v with shape [128]
INFO:transformers.modeling_albert:Loading TF weight bert/embeddings/LayerNorm/gamma with shape [128]
INFO:transformers.modeling_albert:Loading TF weight bert/embeddings/LayerNorm/gamma/adam_m with shape [128]
INFO:transformers.modeling_albert:Loading TF weight bert/embeddings/LayerNorm/gamma/adam_v with shape [128]
INFO:transformers.modeling_albert:Loading TF weight bert/embeddings/position_embeddings with shape [512, 128]
INFO:transformers.modeling_albert:Loading TF weight bert/embeddings/position_embeddings/adam_m with shape [512, 128]
INFO:transformers.modeling_albert:Loading TF weight bert/embeddings/position_embeddings/adam_v with shape [512, 128]
INFO:transformers.modeling_albert:Loading TF weight bert/embeddings/token_type_embeddings with shape [2, 128]
INFO:transformers.modeling_albert:Loading TF weight bert/embeddings/token_type_embeddings/adam_m with shape [2, 128]
INFO:transformers.modeling_albert:Loading TF weight bert/embeddings/token_type_embeddings/adam_v with shape [2, 128]
INFO:transformers.modeling_albert:Loading TF weight bert/embeddings/word_embeddings with shape [30000, 128]
INFO:transformers.modeling_albert:Loading TF weight bert/embeddings/word_embeddings/adam_m with shape [30000, 128]
INFO:transformers.modeling_albert:Loading TF weight bert/embeddings/word_embeddings/adam_v with shape [30000, 128]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/embedding_hidden_mapping_in/bias with shape [4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/embedding_hidden_mapping_in/bias/adam_m with shape [4096]
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INFO:transformers.modeling_albert:Loading TF weight bert/encoder/embedding_hidden_mapping_in/kernel with shape [128, 4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/embedding_hidden_mapping_in/kernel/adam_m with shape [128, 4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/embedding_hidden_mapping_in/kernel/adam_v with shape [128, 4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/LayerNorm/beta with shape [4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/LayerNorm/beta/adam_m with shape [4096]
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INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/LayerNorm/gamma with shape [4096]
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INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/attention_1/output/dense/bias with shape [4096]
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INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/attention_1/output/dense/kernel with shape [4096, 4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/attention_1/output/dense/kernel/adam_m with shape [4096, 4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/attention_1/output/dense/kernel/adam_v with shape [4096, 4096]
INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/attention_1/self/key/bias with shape [4096]
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INFO:transformers.modeling_albert:Loading TF weight bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/output/dense/kernel with shape [16384, 4096]
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INFO:transformers.modeling_albert:Loading TF weight bert/pooler/dense/bias with shape [4096]
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INFO:transformers.modeling_albert:Loading TF weight global_step with shape []
INFO:transformers.modeling_albert:Loading TF weight output_bias with shape [3]
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INFO:transformers.modeling_albert:Loading TF weight output_weights/adam_v with shape [3, 4096]
bert/embeddings/LayerNorm/beta
bert/embeddings/LayerNorm/beta/adam_m
bert/embeddings/LayerNorm/beta/adam_v
bert/embeddings/LayerNorm/gamma
bert/embeddings/LayerNorm/gamma/adam_m
bert/embeddings/LayerNorm/gamma/adam_v
bert/embeddings/position_embeddings
bert/embeddings/position_embeddings/adam_m
bert/embeddings/position_embeddings/adam_v
bert/embeddings/token_type_embeddings
bert/embeddings/token_type_embeddings/adam_m
bert/embeddings/token_type_embeddings/adam_v
bert/embeddings/word_embeddings
bert/embeddings/word_embeddings/adam_m
bert/embeddings/word_embeddings/adam_v
bert/encoder/embedding_hidden_mapping_in/bias
bert/encoder/embedding_hidden_mapping_in/bias/adam_m
bert/encoder/embedding_hidden_mapping_in/bias/adam_v
bert/encoder/embedding_hidden_mapping_in/kernel
bert/encoder/embedding_hidden_mapping_in/kernel/adam_m
bert/encoder/embedding_hidden_mapping_in/kernel/adam_v
bert/encoder/transformer/group_0/inner_group_0/LayerNorm/beta
bert/encoder/transformer/group_0/inner_group_0/LayerNorm/beta/adam_m
bert/encoder/transformer/group_0/inner_group_0/LayerNorm/beta/adam_v
bert/encoder/transformer/group_0/inner_group_0/LayerNorm/gamma
bert/encoder/transformer/group_0/inner_group_0/LayerNorm/gamma/adam_m
bert/encoder/transformer/group_0/inner_group_0/LayerNorm/gamma/adam_v
bert/encoder/transformer/group_0/inner_group_0/LayerNorm_1/beta
bert/encoder/transformer/group_0/inner_group_0/LayerNorm_1/beta/adam_m
bert/encoder/transformer/group_0/inner_group_0/LayerNorm_1/beta/adam_v
bert/encoder/transformer/group_0/inner_group_0/LayerNorm_1/gamma
bert/encoder/transformer/group_0/inner_group_0/LayerNorm_1/gamma/adam_m
bert/encoder/transformer/group_0/inner_group_0/LayerNorm_1/gamma/adam_v
bert/encoder/transformer/group_0/inner_group_0/attention_1/output/dense/bias
bert/encoder/transformer/group_0/inner_group_0/attention_1/output/dense/bias/adam_m
bert/encoder/transformer/group_0/inner_group_0/attention_1/output/dense/bias/adam_v
bert/encoder/transformer/group_0/inner_group_0/attention_1/output/dense/kernel
bert/encoder/transformer/group_0/inner_group_0/attention_1/output/dense/kernel/adam_m
bert/encoder/transformer/group_0/inner_group_0/attention_1/output/dense/kernel/adam_v
bert/encoder/transformer/group_0/inner_group_0/attention_1/self/key/bias
bert/encoder/transformer/group_0/inner_group_0/attention_1/self/key/bias/adam_m
bert/encoder/transformer/group_0/inner_group_0/attention_1/self/key/bias/adam_v
bert/encoder/transformer/group_0/inner_group_0/attention_1/self/key/kernel
bert/encoder/transformer/group_0/inner_group_0/attention_1/self/key/kernel/adam_m
bert/encoder/transformer/group_0/inner_group_0/attention_1/self/key/kernel/adam_v
bert/encoder/transformer/group_0/inner_group_0/attention_1/self/query/bias
bert/encoder/transformer/group_0/inner_group_0/attention_1/self/query/bias/adam_m
bert/encoder/transformer/group_0/inner_group_0/attention_1/self/query/bias/adam_v
bert/encoder/transformer/group_0/inner_group_0/attention_1/self/query/kernel
bert/encoder/transformer/group_0/inner_group_0/attention_1/self/query/kernel/adam_m
bert/encoder/transformer/group_0/inner_group_0/attention_1/self/query/kernel/adam_v
bert/encoder/transformer/group_0/inner_group_0/attention_1/self/value/bias
bert/encoder/transformer/group_0/inner_group_0/attention_1/self/value/bias/adam_m
bert/encoder/transformer/group_0/inner_group_0/attention_1/self/value/bias/adam_v
bert/encoder/transformer/group_0/inner_group_0/attention_1/self/value/kernel
bert/encoder/transformer/group_0/inner_group_0/attention_1/self/value/kernel/adam_m
bert/encoder/transformer/group_0/inner_group_0/attention_1/self/value/kernel/adam_v
bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/dense/bias
bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/dense/bias/adam_m
bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/dense/bias/adam_v
bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/dense/kernel
bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/dense/kernel/adam_m
bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/dense/kernel/adam_v
bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/output/dense/bias
bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/output/dense/bias/adam_m
bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/output/dense/bias/adam_v
bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/output/dense/kernel
bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/output/dense/kernel/adam_m
bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/output/dense/kernel/adam_v
bert/pooler/dense/bias
bert/pooler/dense/bias/adam_m
bert/pooler/dense/bias/adam_v
bert/pooler/dense/kernel
bert/pooler/dense/kernel/adam_m
bert/pooler/dense/kernel/adam_v
global_step
output_bias
output_bias/adam_m
output_bias/adam_v
output_weights
output_weights/adam_m
output_weights/adam_v
Initialize PyTorch weight ['albert', 'embeddings', 'LayerNorm', 'beta'] from bert/embeddings/LayerNorm/beta
INFO:transformers.modeling_albert:Skipping albert/embeddings/LayerNorm/beta/adam_m
INFO:transformers.modeling_albert:Skipping albert/embeddings/LayerNorm/beta/adam_v
Initialize PyTorch weight ['albert', 'embeddings', 'LayerNorm', 'gamma'] from bert/embeddings/LayerNorm/gamma
INFO:transformers.modeling_albert:Skipping albert/embeddings/LayerNorm/gamma/adam_m
INFO:transformers.modeling_albert:Skipping albert/embeddings/LayerNorm/gamma/adam_v
Initialize PyTorch weight ['albert', 'embeddings', 'position_embeddings'] from bert/embeddings/position_embeddings
INFO:transformers.modeling_albert:Skipping albert/embeddings/position_embeddings/adam_m
INFO:transformers.modeling_albert:Skipping albert/embeddings/position_embeddings/adam_v
Initialize PyTorch weight ['albert', 'embeddings', 'token_type_embeddings'] from bert/embeddings/token_type_embeddings
INFO:transformers.modeling_albert:Skipping albert/embeddings/token_type_embeddings/adam_m
INFO:transformers.modeling_albert:Skipping albert/embeddings/token_type_embeddings/adam_v
Initialize PyTorch weight ['albert', 'embeddings', 'word_embeddings'] from bert/embeddings/word_embeddings
INFO:transformers.modeling_albert:Skipping albert/embeddings/word_embeddings/adam_m
INFO:transformers.modeling_albert:Skipping albert/embeddings/word_embeddings/adam_v
Initialize PyTorch weight ['albert', 'encoder', 'embedding_hidden_mapping_in', 'bias'] from bert/encoder/embedding_hidden_mapping_in/bias
INFO:transformers.modeling_albert:Skipping albert/encoder/embedding_hidden_mapping_in/bias/adam_m
INFO:transformers.modeling_albert:Skipping albert/encoder/embedding_hidden_mapping_in/bias/adam_v
Initialize PyTorch weight ['albert', 'encoder', 'embedding_hidden_mapping_in', 'kernel'] from bert/encoder/embedding_hidden_mapping_in/kernel
INFO:transformers.modeling_albert:Skipping albert/encoder/embedding_hidden_mapping_in/kernel/adam_m
INFO:transformers.modeling_albert:Skipping albert/encoder/embedding_hidden_mapping_in/kernel/adam_v
Initialize PyTorch weight ['albert', 'encoder', 'albert_layer_groups', '0', 'albert_layers', '0', 'attention', 'LayerNorm', 'beta'] from bert/encoder/transformer/group_0/inner_group_0/LayerNorm/beta
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/LayerNorm/beta/adam_m
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/LayerNorm/beta/adam_v
Initialize PyTorch weight ['albert', 'encoder', 'albert_layer_groups', '0', 'albert_layers', '0', 'attention', 'LayerNorm', 'gamma'] from bert/encoder/transformer/group_0/inner_group_0/LayerNorm/gamma
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/LayerNorm/gamma/adam_m
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/LayerNorm/gamma/adam_v
Initialize PyTorch weight ['albert', 'encoder', 'albert_layer_groups', '0', 'albert_layers', '0', 'full_layer_layer_norm', 'beta'] from bert/encoder/transformer/group_0/inner_group_0/LayerNorm_1/beta
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/full_layer_layer_norm/beta/adam_m
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/full_layer_layer_norm/beta/adam_v
Initialize PyTorch weight ['albert', 'encoder', 'albert_layer_groups', '0', 'albert_layers', '0', 'full_layer_layer_norm', 'gamma'] from bert/encoder/transformer/group_0/inner_group_0/LayerNorm_1/gamma
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/full_layer_layer_norm/gamma/adam_m
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/full_layer_layer_norm/gamma/adam_v
Initialize PyTorch weight ['albert', 'encoder', 'albert_layer_groups', '0', 'albert_layers', '0', 'attention', 'dense', 'bias'] from bert/encoder/transformer/group_0/inner_group_0/attention_1/output/dense/bias
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/dense/bias/adam_m
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/dense/bias/adam_v
Initialize PyTorch weight ['albert', 'encoder', 'albert_layer_groups', '0', 'albert_layers', '0', 'attention', 'dense', 'kernel'] from bert/encoder/transformer/group_0/inner_group_0/attention_1/output/dense/kernel
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/dense/kernel/adam_m
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/dense/kernel/adam_v
Initialize PyTorch weight ['albert', 'encoder', 'albert_layer_groups', '0', 'albert_layers', '0', 'attention', 'key', 'bias'] from bert/encoder/transformer/group_0/inner_group_0/attention_1/self/key/bias
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/key/bias/adam_m
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/key/bias/adam_v
Initialize PyTorch weight ['albert', 'encoder', 'albert_layer_groups', '0', 'albert_layers', '0', 'attention', 'key', 'kernel'] from bert/encoder/transformer/group_0/inner_group_0/attention_1/self/key/kernel
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/key/kernel/adam_m
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/key/kernel/adam_v
Initialize PyTorch weight ['albert', 'encoder', 'albert_layer_groups', '0', 'albert_layers', '0', 'attention', 'query', 'bias'] from bert/encoder/transformer/group_0/inner_group_0/attention_1/self/query/bias
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/query/bias/adam_m
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/query/bias/adam_v
Initialize PyTorch weight ['albert', 'encoder', 'albert_layer_groups', '0', 'albert_layers', '0', 'attention', 'query', 'kernel'] from bert/encoder/transformer/group_0/inner_group_0/attention_1/self/query/kernel
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/query/kernel/adam_m
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/query/kernel/adam_v
Initialize PyTorch weight ['albert', 'encoder', 'albert_layer_groups', '0', 'albert_layers', '0', 'attention', 'value', 'bias'] from bert/encoder/transformer/group_0/inner_group_0/attention_1/self/value/bias
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/value/bias/adam_m
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/value/bias/adam_v
Initialize PyTorch weight ['albert', 'encoder', 'albert_layer_groups', '0', 'albert_layers', '0', 'attention', 'value', 'kernel'] from bert/encoder/transformer/group_0/inner_group_0/attention_1/self/value/kernel
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/value/kernel/adam_m
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/attention/value/kernel/adam_v
Initialize PyTorch weight ['albert', 'encoder', 'albert_layer_groups', '0', 'albert_layers', '0', 'ffn', 'bias'] from bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/dense/bias
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/ffn/bias/adam_m
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/ffn/bias/adam_v
Initialize PyTorch weight ['albert', 'encoder', 'albert_layer_groups', '0', 'albert_layers', '0', 'ffn', 'kernel'] from bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/dense/kernel
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/ffn/kernel/adam_m
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/ffn/kernel/adam_v
Initialize PyTorch weight ['albert', 'encoder', 'albert_layer_groups', '0', 'albert_layers', '0', 'ffn_output', 'bias'] from bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/output/dense/bias
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/ffn_output/bias/adam_m
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/ffn_output/bias/adam_v
Initialize PyTorch weight ['albert', 'encoder', 'albert_layer_groups', '0', 'albert_layers', '0', 'ffn_output', 'kernel'] from bert/encoder/transformer/group_0/inner_group_0/ffn_1/intermediate/output/dense/kernel
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/ffn_output/kernel/adam_m
INFO:transformers.modeling_albert:Skipping albert/encoder/albert_layer_groups/0/albert_layers/0/ffn_output/kernel/adam_v
Initialize PyTorch weight ['albert', 'pooler', 'bias'] from bert/pooler/dense/bias
INFO:transformers.modeling_albert:Skipping albert/pooler/bias/adam_m
INFO:transformers.modeling_albert:Skipping albert/pooler/bias/adam_v
Initialize PyTorch weight ['albert', 'pooler', 'kernel'] from bert/pooler/dense/kernel
INFO:transformers.modeling_albert:Skipping albert/pooler/kernel/adam_m
INFO:transformers.modeling_albert:Skipping albert/pooler/kernel/adam_v
INFO:transformers.modeling_albert:Skipping global_step
INFO:transformers.modeling_albert:Skipping classifier/output_bias
Traceback (most recent call last):
  File "/content/transformers/src/transformers/convert_albert_original_tf_checkpoint_to_pytorch.py", line 61, in <module>
    convert_tf_checkpoint_to_pytorch(args.tf_checkpoint_path, args.albert_config_file, args.pytorch_dump_path)
  File "/content/transformers/src/transformers/convert_albert_original_tf_checkpoint_to_pytorch.py", line 36, in convert_tf_checkpoint_to_pytorch
    load_tf_weights_in_albert(model, config, tf_checkpoint_path)
  File "/content/drive/My Drive/transformers/src/transformers/modeling_albert.py", line 140, in load_tf_weights_in_albert
    pointer = getattr(pointer, "bias")
  File "/usr/local/lib/python3.6/dist-packages/torch/nn/modules/module.py", line 576, in __getattr__
    type(self).__name__, name))
AttributeError: 'AlbertForQuestionAnswering' object has no attribute 'bias'
```
## Expected behavior

This behavior only happen with a fine-tuned model on SQUAD or GLUE. I know and I managed to convert TF checkpoint without being fine-tuned on TF unit and they work fine. However, if I fine-tune my model using TF on SQUAD, then I can't convert the checkpoint.

## Environment info
Google Colab
     
- `transformers` version: latest 
- Platform: Google Colab
- Python version: 3.6.9
- PyTorch version (GPU?):
- Tensorflow version (GPU?): 
- Using GPU in script?: Yes
- Using distributed or parallel set-up in script?: No


This problem has not been fixed for a long time. please have a look at this post:
https://github.com/huggingface/transformers/issues/2006
Same issue here. i still have an error. could you write answer here?<|||||>our hero LysandreJik assigned this problem to himself. Let's have confidence in him to solve it (:<|||||>You fine-tuned your TF checkpoint using the original implementation, is that correct?<|||||>Thanks you, but i find way resolved my problem. i fine-tuning albert with pre-train load from checkpoint tf so i just  convert to bin model and using hugging face abtract class to load . Done!<|||||>Yes, I fine-tuned it using python3 albert/run_squad_v2.py with adam optimizer. Then I tried to convert squad checkpoint using the hugging face transformer model.  I will appreciate your help because I am waiting for two weeks for this problem to be solved.<|||||>> Thanks you, but i find way resolved my problem. i fine-tuning albert with pre-train load from checkpoint tf so i just convert to bin model and using hugging face abtract class to load . Done!

is this checkpoint find-tuned on SQUAD ? because I have no problem converting ALBERT checkpoint that was not fine-tuned on downstream tasks.<|||||>you can try function in repo to convert checkpoint tf to pytorch bin model: https://github.com/lonePatient/albert_pytorch.git<|||||>This feature is not currently supported by our conversion scripts. I can take a look later this week, or you can try modifying the code yourself:

- Change from `AlbertForPreTraining` to `AlbertForQuestionAnswering` in the [conversion file](https://github.com/huggingface/transformers/blob/master/src/transformers/convert_albert_original_tf_checkpoint_to_pytorch.py).
- Rename the weights in your model to those of our `AlbertForQuestionAnswering` by replacing the layers like it is done in [this method](https://github.com/huggingface/transformers/blob/master/src/transformers/modeling_albert.py#L79-L106). Something like `name = name.replace("classifier", "qa_outputs")` would probably work.

Please note that this would work in the case where the ALBERT official implementation has the same Question Answering model as we do (that is, a single linear layer on top of the transformer). If there isn't, you would need to create a model similar to `AlbertForQuestionAnswering` but with the correct head.<|||||>> This feature is not currently supported by our conversion scripts. I can take a look later this week, or you can try modifying the code yourself:
> 
> * Change from `AlbertForPreTraining` to `AlbertForQuestionAnswering` in the [conversion file](https://github.com/huggingface/transformers/blob/master/src/transformers/convert_albert_original_tf_checkpoint_to_pytorch.py).
> * Rename the weights in your model to those of our `AlbertForQuestionAnswering` by replacing the layers like it is done in [this method](https://github.com/huggingface/transformers/blob/master/src/transformers/modeling_albert.py#L79-L106). Something like `name = name.replace("classifier", "qa_outputs")` would probably work.
> 
> Please note that this would work in the case where the ALBERT official implementation has the same Question Answering model as we do (that is, a single linear layer on top of the transformer). If there isn't, you would need to create a model similar to `AlbertForQuestionAnswering` but with the correct head.

Problem still exists . A message saying "AttributeError: 'AlbertForQuestionAnswering' object has no attribute 'shape'" appears even though I did all what you said. I think it's worth fixing it by you later this week. Google Colab offers TPUv3 which has 128GB and Hugging face transformers only support GPU where google collab offers P100 that has 16GB. That is an 8x performance boost for TPU so it will take me days to fine-tune it using transformers library only with GPU.<|||||>This issue has been automatically marked as stale because it has not had recent activity. It will be closed if no further activity occurs. Thank you for your contributions.
