transformers pytorch hybridbert text-classification generated_from_trainer en dataset:glue base_model:gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48 base_model:finetune:gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48
datasets:
- glue
language:
- en
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: hBERTv1_new_pretrain_w_init_48_ver2_mnli
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE MNLI
      type: glue
      config: mnli
      split: validation_matched
      args: mnli
    metrics:
    - type: accuracy
      value: 0.459519934906428
      name: Accuracy
---

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# hBERTv1_new_pretrain_w_init_48_ver2_mnli

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_wt_init_48) on the GLUE MNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0270
- Accuracy: 0.4595

## 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: 64
- eval_batch_size: 64
- seed: 10
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.0624        | 1.0   | 6136  | 1.0715          | 0.3840   |
| 1.0497        | 2.0   | 12272 | 1.0548          | 0.4072   |
| 1.0421        | 3.0   | 18408 | 1.0476          | 0.4432   |
| 1.0485        | 4.0   | 24544 | 1.0547          | 0.4414   |
| 1.0473        | 5.0   | 30680 | 1.0516          | 0.4553   |
| 1.0498        | 6.0   | 36816 | 1.0556          | 0.4427   |
| 1.0531        | 7.0   | 42952 | 1.0556          | 0.4381   |
| 1.0609        | 8.0   | 49088 | 1.0687          | 0.4028   |


### Framework versions

- Transformers 4.34.0
- Pytorch 1.14.0a0+410ce96
- Datasets 2.14.5
- Tokenizers 0.14.1
