---
license: mit
base_model: Amna100/PreTraining-MLM
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: fold_2
  results: []
---

<!-- 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_2

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: 0.0099
- Precision: 0.7059
- Recall: 0.7018
- F1: 0.7038
- Accuracy: 0.9974

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0278        | 1.0   | 635  | 0.0115          | 0.7523    | 0.4795 | 0.5857 | 0.9966   |
| 0.0084        | 2.0   | 1270 | 0.0091          | 0.7118    | 0.7222 | 0.7170 | 0.9974   |
| 0.0057        | 3.0   | 1905 | 0.0099          | 0.7059    | 0.7018 | 0.7038 | 0.9974   |


### Framework versions

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