
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# bert_finetune_classification

This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1339

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 30
- num_epochs: 9

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.0748        | 1.0   | 417  | 0.0957          |
| 0.0517        | 2.0   | 834  | 0.0880          |
| 0.0631        | 3.0   | 1251 | 0.0736          |
| 0.0048        | 4.0   | 1669 | 0.0795          |
| 0.0457        | 5.0   | 2086 | 0.0861          |
| 0.0016        | 6.0   | 2503 | 0.1086          |
| 0.0482        | 7.0   | 2920 | 0.1073          |
| 0.0483        | 8.0   | 3338 | 0.1224          |
| 0.0286        | 8.99  | 3753 | 0.1339          |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.0.0+cu117
- Datasets 2.14.5
- Tokenizers 0.14.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "base_model": "bert-base-cased", "model-index": [{"name": "bert_finetune_classification", "results": []}]}
transformers pytorch bert text-classification generated_from_trainer base_model:bert-base-cased license:apache-2.0 autotrain_compatible endpoints_compatible region:us