| --- |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - f1 |
| - recall |
| - precision |
| model-index: |
| - name: mixed_model_combined_data |
| 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/yassmenyoussef55-arete-global/huggingface/runs/4lnhrv4o) |
| # mixed_model_combined_data |
| |
| This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.3112 |
| - Accuracy: 0.8954 |
| - F1: 0.8944 |
| - Recall: 0.8954 |
| - Precision: 0.8953 |
| |
| ## 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: 0.0001 |
| - train_batch_size: 4 |
| - eval_batch_size: 4 |
| - seed: 42 |
| - gradient_accumulation_steps: 8 |
| - total_train_batch_size: 32 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - training_steps: 849 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision | |
| |:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:------:|:---------:| |
| | 0.66 | 0.9982 | 212 | 0.7179 | 0.7648 | 0.7546 | 0.7648 | 0.7864 | |
| | 0.4943 | 1.9965 | 424 | 0.5750 | 0.8136 | 0.8106 | 0.8136 | 0.8352 | |
| | 0.2822 | 2.9994 | 637 | 0.3672 | 0.8713 | 0.8696 | 0.8713 | 0.8743 | |
| | 0.1882 | 3.9976 | 849 | 0.3112 | 0.8954 | 0.8944 | 0.8954 | 0.8953 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.42.3 |
| - Pytorch 2.1.2 |
| - Datasets 2.20.0 |
| - Tokenizers 0.19.1 |
| |
