---
license: mit
base_model: Amna100/PreTraining-MLM
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: fold_0
  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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/amnasaeed100/FineTuning-ADE-change1/runs/94wgcdtp)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/amnasaeed100/FineTuning-ADE-change1/runs/8g0cixov)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/amnasaeed100/FineTuning-ADE-change1/runs/05nc4r5u)
# fold_0

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: 0.0130
- Precision: 0.1834
- Recall: 0.3042
- F1: 0.5248
- Pr Auc: 0.6999
- Roc Auc: 0.9149

## 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: 5e-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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Pr Auc | Roc Auc |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:------:|:-------:|
| 0.0281        | 1.0   | 630  | 0.0113          | 0.3745    | 0.9507 | 0.7320 | 0.6813 | 0.9278  |
| 0.009         | 2.0   | 1260 | 0.0108          | 0.5987    | 0.1560 | 0.1560 | 0.5519 | 0.9242  |
| 0.0061        | 3.0   | 1890 | 0.0110          | 0.0581    | 0.8662 | 0.6011 | 0.6682 | 0.9283  |
| 0.0012        | 4.0   | 2520 | 0.0122          | 0.7081    | 0.0206 | 0.9699 | 0.7090 | 0.9146  |
| 0.0006        | 5.0   | 3150 | 0.0130          | 0.8324    | 0.2123 | 0.1818 | 0.6999 | 0.9149  |


### Framework versions

- Transformers 4.41.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1