| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: Qwen/Qwen2-1.5B |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: fine_tuned_yelp |
| 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. --> |
|
|
| # fine_tuned_yelp |
|
|
| This model is a fine-tuned version of [Qwen/Qwen2-1.5B](https://huggingface.co/Qwen/Qwen2-1.5B) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.2855 |
| - Accuracy: 0.9328 |
|
|
| ## 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: 2e-05 |
| - train_batch_size: 8 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 3 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:------:|:----:|:---------------:|:--------:| |
| | 0.927 | 0.0170 | 100 | 0.4956 | 0.7806 | |
| | 0.5634 | 0.0340 | 200 | 0.4637 | 0.8044 | |
| | 0.4876 | 0.0509 | 300 | 0.7024 | 0.8648 | |
| | 0.4179 | 0.0679 | 400 | 0.3941 | 0.8944 | |
| | 0.4397 | 0.0849 | 500 | 0.5622 | 0.8291 | |
| | 0.3985 | 0.1019 | 600 | 0.3185 | 0.8997 | |
| | 0.4607 | 0.1188 | 700 | 0.4404 | 0.8942 | |
| | 0.4023 | 0.1358 | 800 | 0.2967 | 0.9091 | |
| | 0.3185 | 0.1528 | 900 | 0.3033 | 0.8980 | |
| | 0.335 | 0.1698 | 1000 | 0.2653 | 0.9232 | |
| | 0.3665 | 0.1868 | 1100 | 0.2280 | 0.9246 | |
| | 0.3033 | 0.2037 | 1200 | 0.1975 | 0.9320 | |
| | 0.2578 | 0.2207 | 1300 | 0.2171 | 0.9341 | |
| | 0.3417 | 0.2377 | 1400 | 0.2497 | 0.9301 | |
| | 0.3222 | 0.2547 | 1500 | 0.2855 | 0.9328 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.49.0 |
| - Pytorch 2.6.0+cu126 |
| - Datasets 3.3.2 |
| - Tokenizers 0.21.0 |
|
|
