| --- |
| license: mit |
| base_model: Amna100/PreTraining-MLM |
| tags: |
| - generated_from_trainer |
| metrics: |
| - precision |
| - recall |
| - f1 |
| - accuracy |
| model-index: |
| - name: fold_4 |
| 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-change2/runs/zkyqf4w8) |
| [<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-change2/runs/n6lnsbeg) |
| [<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-change2/runs/k9jhon43) |
| [<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-change2/runs/67sviuwh) |
| [<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-change2/runs/e4zmtw0z) |
| [<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-change2/runs/ykmsii48) |
| [<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-change2/runs/hrdcpnd9) |
| # 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: 0.0104 |
| - Precision: 0.6792 |
| - Recall: 0.5870 |
| - F1: 0.6297 |
| - Accuracy: 0.9993 |
| - Roc Auc: 0.9967 |
| - Pr Auc: 0.9999 |
| |
| ## 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 | Accuracy | Roc Auc | Pr Auc | |
| |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:-------:|:------:| |
| | 0.0252 | 1.0 | 711 | 0.0159 | 0.4538 | 0.6413 | 0.5315 | 0.9988 | 0.9944 | 0.9998 | |
| | 0.0095 | 2.0 | 1422 | 0.0104 | 0.6792 | 0.5870 | 0.6297 | 0.9993 | 0.9967 | 0.9999 | |
| | 0.003 | 3.0 | 2133 | 0.0106 | 0.6432 | 0.6957 | 0.6684 | 0.9993 | 0.9973 | 0.9999 | |
| | 0.0024 | 4.0 | 2844 | 0.0126 | 0.7006 | 0.6739 | 0.6870 | 0.9994 | 0.9960 | 0.9999 | |
| | 0.0004 | 5.0 | 3555 | 0.0148 | 0.7239 | 0.6413 | 0.6801 | 0.9994 | 0.9954 | 0.9999 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.42.0.dev0 |
| - Pytorch 2.3.0+cu121 |
| - Datasets 2.19.1 |
| - Tokenizers 0.19.1 |
| |
