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--- |
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license: mit |
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base_model: Amna100/PreTraining-MLM |
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tags: |
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- generated_from_trainer |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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model-index: |
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- name: fold_0 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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[<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) |
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[<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) |
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[<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) |
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# fold_0 |
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This model is a fine-tuned version of [Amna100/PreTraining-MLM](https://huggingface.co/Amna100/PreTraining-MLM) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0105 |
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- Precision: 0.7006 |
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- Recall: 0.5978 |
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- F1: 0.6452 |
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- Accuracy: 0.9993 |
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- Roc Auc: 0.9968 |
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- Pr Auc: 0.9999 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 5e-05 |
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- train_batch_size: 5 |
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- eval_batch_size: 5 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | Roc Auc | Pr Auc | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|:-------:|:------:| |
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| 0.0265 | 1.0 | 711 | 0.0162 | 0.4318 | 0.6196 | 0.5089 | 0.9987 | 0.9959 | 0.9998 | |
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| 0.0098 | 2.0 | 1422 | 0.0105 | 0.7006 | 0.5978 | 0.6452 | 0.9993 | 0.9968 | 0.9999 | |
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| 0.0038 | 3.0 | 2133 | 0.0123 | 0.6169 | 0.6739 | 0.6442 | 0.9992 | 0.9966 | 0.9999 | |
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| 0.0022 | 4.0 | 2844 | 0.0138 | 0.7006 | 0.6359 | 0.6667 | 0.9994 | 0.9963 | 0.9999 | |
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| 0.0004 | 5.0 | 3555 | 0.0151 | 0.7262 | 0.6630 | 0.6932 | 0.9994 | 0.9957 | 0.9999 | |
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### Framework versions |
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- Transformers 4.42.0.dev0 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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