transformers pytorch tensorboard hybridbert text-classification generated_from_trainer en dataset:glue model-index autotrain_compatible endpoints_compatible region:us
---
datasets:
- glue
language:
- en
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: hBERTv2_new_pretrain_48_KD_w_init_sst2
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE SST2
      type: glue
      config: sst2
      split: validation
      args: sst2
    metrics:
    - type: accuracy
      value: 0.8394495412844036
      name: Accuracy
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# hBERTv2_new_pretrain_48_KD_w_init_sst2

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v2_complete_training_new_48_KD_wt_init](https://huggingface.co/gokuls/bert_12_layer_model_v2_complete_training_new_48_KD_wt_init) on the GLUE SST2 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4188
- Accuracy: 0.8394

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 4e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 10
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.3594        | 1.0   | 527  | 0.4188          | 0.8394   |
| 0.2344        | 2.0   | 1054 | 0.5086          | 0.8337   |
| 0.2012        | 3.0   | 1581 | 0.5127          | 0.8177   |
| 0.1723        | 4.0   | 2108 | 0.4814          | 0.8200   |
| 0.1425        | 5.0   | 2635 | 0.4872          | 0.8314   |
| 0.12          | 6.0   | 3162 | 0.5835          | 0.8222   |


### Framework versions

- Transformers 4.30.2
- Pytorch 1.14.0a0+410ce96
- Datasets 2.13.0
- Tokenizers 0.13.3
