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---
license: mit
base_model: Amna100/PreTraining-MLM
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: fold_1
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/wbresearch/FineTuning-ADE-DropOUT/runs/rw6sjeap)
[<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/wbresearch/FineTuning-ADE-DropOUT/runs/g4pyaj7k)
[<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/wbresearch/FineTuning-ADE-DropOUT/runs/t4il24wd)
[<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/wbresearch/FineTuning-ADE-DropOUT/runs/qf2ywrxq)
[<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/wbresearch/FineTuning-ADE-DropOUT/runs/9xmjfnoc)
# fold_1
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: 0.0113
- Precision: 0.7155
- Recall: 0.7233
- F1: 0.7194
- Accuracy: 0.9993
- Roc Auc: 0.9952
- 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | Roc Auc | Pr Auc |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:-------:|:------:|
| 0.0241 | 1.0 | 632 | 0.0123 | 0.6317 | 0.6427 | 0.6371 | 0.9991 | 0.9958 | 0.9999 |
| 0.0098 | 2.0 | 1264 | 0.0114 | 0.8436 | 0.6580 | 0.7393 | 0.9994 | 0.9946 | 0.9998 |
| 0.0062 | 3.0 | 1896 | 0.0113 | 0.7155 | 0.7233 | 0.7194 | 0.9993 | 0.9952 | 0.9999 |
| 0.0021 | 4.0 | 2528 | 0.0132 | 0.7990 | 0.6841 | 0.7371 | 0.9993 | 0.9944 | 0.9998 |
| 0.0013 | 5.0 | 3160 | 0.0145 | 0.7783 | 0.7037 | 0.7391 | 0.9993 | 0.9956 | 0.9998 |
| 0.001 | 6.0 | 3792 | 0.0159 | 0.7730 | 0.7495 | 0.7611 | 0.9994 | 0.9958 | 0.9998 |
| 0.0004 | 7.0 | 4424 | 0.0143 | 0.7104 | 0.7908 | 0.7485 | 0.9993 | 0.9964 | 0.9999 |
| 0.0002 | 8.0 | 5056 | 0.0173 | 0.8005 | 0.7255 | 0.7611 | 0.9994 | 0.9951 | 0.9999 |
| 0.0002 | 9.0 | 5688 | 0.0176 | 0.7981 | 0.7233 | 0.7589 | 0.9993 | 0.9948 | 0.9999 |
### Framework versions
- Transformers 4.41.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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