transformers pytorch hybridbert text-classification generated_from_trainer en dataset:glue base_model:gokuls/bert_12_layer_model_v1_complete_training_new_48 base_model:finetune:gokuls/bert_12_layer_model_v1_complete_training_new_48 model-index autotrain_compatible endpoints_compatible region:us
---
base_model: gokuls/bert_12_layer_model_v1_complete_training_new_48
datasets:
- glue
language:
- en
metrics:
- accuracy
tags:
- generated_from_trainer
model-index:
- name: hBERTv1_new_pretrain_48_ver2_wnli
  results:
  - task:
      type: text-classification
      name: Text Classification
    dataset:
      name: GLUE WNLI
      type: glue
      config: wnli
      split: validation
      args: wnli
    metrics:
    - type: accuracy
      value: 0.43661971830985913
      name: Accuracy
---

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# hBERTv1_new_pretrain_48_ver2_wnli

This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_48](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_48) on the GLUE WNLI dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7002
- Accuracy: 0.4366

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7332        | 1.0   | 10   | 0.7386          | 0.4366   |
| 0.7093        | 2.0   | 20   | 0.7002          | 0.4366   |
| 0.7175        | 3.0   | 30   | 0.7295          | 0.4366   |
| 0.7044        | 4.0   | 40   | 0.7007          | 0.4366   |
| 0.6906        | 5.0   | 50   | 0.7484          | 0.4366   |
| 0.7095        | 6.0   | 60   | 0.7177          | 0.4366   |
| 0.7201        | 7.0   | 70   | 0.7029          | 0.5634   |


### Framework versions

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