| --- |
| library_name: transformers |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: gpt-mqa-RoPE |
| 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. --> |
|
|
| # gpt-mqa-RoPE |
|
|
| 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: 6.0885 |
|
|
| ## Model description |
|
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| 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: 0.0003 |
| - train_batch_size: 128 |
| - eval_batch_size: 128 |
| - seed: 20 |
| - gradient_accumulation_steps: 4 |
| - total_train_batch_size: 512 |
| - 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: 106 |
| - training_steps: 1060 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:------:|:----:|:---------------:| |
| | 9.5007 | 0.0590 | 106 | 9.2225 | |
| | 7.6938 | 0.1179 | 212 | 7.6025 | |
| | 7.0385 | 0.1769 | 318 | 6.9495 | |
| | 6.6472 | 0.2359 | 424 | 6.5905 | |
| | 6.4123 | 0.2948 | 530 | 6.3711 | |
| | 6.2808 | 0.3538 | 636 | 6.2347 | |
| | 6.1927 | 0.4127 | 742 | 6.1516 | |
| | 6.1486 | 0.4717 | 848 | 6.1083 | |
| | 6.1331 | 0.5307 | 954 | 6.0914 | |
| | 6.1282 | 0.5896 | 1060 | 6.0885 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 5.5.4 |
| - Pytorch 2.11.0+cu130 |
| - Datasets 4.8.4 |
| - Tokenizers 0.22.2 |
| |
