|
--- |
|
license: mit |
|
base_model: Amna100/PreTraining-MLM |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- precision |
|
- recall |
|
- f1 |
|
- accuracy |
|
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-Repeatedfold/runs/lvieenf2) |
|
# 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: 0.0427 |
|
- Precision: 0.0 |
|
- Recall: 0.0 |
|
- F1: 0.0 |
|
- Accuracy: 0.9986 |
|
- Roc Auc: 0.7183 |
|
- Pr Auc: 0.9951 |
|
|
|
## 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: 10 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | Roc Auc | Pr Auc | |
|
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|:-------:|:------:| |
|
| 0.0452 | 1.0 | 632 | 0.0427 | 0.0 | 0.0 | 0.0 | 0.9986 | 0.7183 | 0.9951 | |
|
| 0.0389 | 2.0 | 1264 | 0.0447 | 0.0 | 0.0 | 0.0 | 0.9986 | 0.6241 | 0.9937 | |
|
| 0.0394 | 3.0 | 1896 | 0.0444 | 0.0 | 0.0 | 0.0 | 0.9986 | 0.6131 | 0.9934 | |
|
| 0.0388 | 4.0 | 2528 | 0.0445 | 0.0 | 0.0 | 0.0 | 0.9986 | 0.6169 | 0.9938 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.41.0.dev0 |
|
- Pytorch 2.2.1+cu121 |
|
- Datasets 2.19.1 |
|
- Tokenizers 0.19.1 |
|
|
