---
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: BERT_test_graident_accumulation_test3_finetuned
  results: []
---

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# BERT_test_graident_accumulation_test3_finetuned

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8880
- Accuracy: 0.6140

## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.96  | 24   | 0.8680          | 0.6190   |
| No log        | 1.97  | 49   | 0.8866          | 0.6165   |
| No log        | 2.89  | 72   | 0.8880          | 0.6140   |


### Framework versions

- Transformers 4.36.0
- Pytorch 2.1.1+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0