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# bert_finetune_prompt_classification

This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1537

## 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: 12

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.945         | 1.0   | 33   | 0.9316          |
| 0.5897        | 1.99  | 66   | 0.3983          |
| 0.2354        | 2.99  | 99   | 0.2213          |
| 0.237         | 3.98  | 132  | 0.1955          |
| 0.2126        | 4.98  | 165  | 0.1485          |
| 0.124         | 5.98  | 198  | 0.1412          |
| 0.1857        | 6.97  | 231  | 0.1540          |
| 0.108         | 8.0   | 265  | 0.1602          |
| 0.0801        | 9.0   | 298  | 0.1561          |
| 0.0421        | 9.99  | 331  | 0.1430          |
| 0.015         | 10.99 | 364  | 0.1480          |
| 0.0113        | 11.95 | 396  | 0.1537          |


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