| --- |
| library_name: transformers |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: HybridModelScratch_ |
| 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. --> |
|
|
| # HybridModelScratch_ |
|
|
| 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: 5.2920 |
| - Accuracy: 0.2203 |
|
|
| ## 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: 64 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 256 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_steps: 150 |
| - training_steps: 1000 |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 32.0977 | 0.1 | 100 | 7.3025 | 0.1141 | |
| | 26.0238 | 0.2 | 200 | 6.3336 | 0.1618 | |
| | 24.2338 | 0.3 | 300 | 5.9560 | 0.1830 | |
| | 23.2729 | 0.4 | 400 | 5.7180 | 0.1967 | |
| | 22.5651 | 0.5 | 500 | 5.5544 | 0.2059 | |
| | 22.0473 | 0.6 | 600 | 5.4359 | 0.2119 | |
| | 21.7227 | 0.7 | 700 | 5.3620 | 0.2162 | |
| | 21.4768 | 0.8 | 800 | 5.3150 | 0.2189 | |
| | 21.3548 | 0.9 | 900 | 5.2958 | 0.2200 | |
| | 21.3675 | 1.0 | 1000 | 5.2920 | 0.2203 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.56.0 |
| - Pytorch 2.8.0+cu129 |
| - Datasets 5.0.0 |
| - Tokenizers 0.22.0 |
| |
