
<!-- 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. -->

# fold_4

This model is a fine-tuned version of [Amna100/PreTraining-MLM](https://huggingface.co/Amna100/PreTraining-MLM) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0115
- Precision: 0.7679
- Recall: 0.7116
- F1: 0.7387
- Accuracy: 0.9972

## 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: 5
- eval_batch_size: 5
- seed: 42
- 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 | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0287        | 1.0   | 636  | 0.0124          | 0.6534    | 0.5839 | 0.6167 | 0.9963   |
| 0.01          | 2.0   | 1272 | 0.0115          | 0.7736    | 0.6383 | 0.6995 | 0.9968   |
| 0.0062        | 3.0   | 1908 | 0.0115          | 0.7679    | 0.7116 | 0.7387 | 0.9972   |


### Framework versions

- Transformers 4.37.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0

{"license": "mit", "tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "Amna100/PreTraining-MLM", "model-index": [{"name": "fold_4", "results": []}]}
transformers safetensors deberta token-classification generated_from_trainer base_model:Amna100/PreTraining-MLM license:mit autotrain_compatible endpoints_compatible region:us