| --- |
| base_model: Qwen/Qwen2.5-0.5B-Instruct |
| license: apache-2.0 |
| metrics: |
| - accuracy |
| - f1 |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: twt-probe |
| 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. --> |
|
|
| # twt-probe |
|
|
| This model is a fine-tuned version of [Qwen/Qwen2.5-0.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.1094 |
| - Accuracy: 0.9815 |
| - F1: 0.9906 |
|
|
| ## Model description |
|
|
| More information needed |
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|
| ## 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: 2e-05 |
| - train_batch_size: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 3 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
| | 0.188 | 1.0 | 2378 | 0.1183 | 0.9765 | 0.9880 | |
| | 0.1216 | 2.0 | 4756 | 0.1067 | 0.9815 | 0.9906 | |
| | 0.1278 | 3.0 | 7134 | 0.1094 | 0.9815 | 0.9906 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.43.0 |
| - Pytorch 2.3.0+cu121 |
| - Datasets 2.20.0 |
| - Tokenizers 0.19.1 |
| |
