| --- |
| license: apache-2.0 |
| base_model: Pipper/SolCoder |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: SolCoder |
| 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. --> |
|
|
| # SolCoder |
|
|
| This model is a fine-tuned version of [Pipper/SolCoder](https://huggingface.co/Pipper/SolCoder) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.5568 |
|
|
| ## 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: 37 |
| - eval_batch_size: 37 |
| - seed: 100 |
| - distributed_type: multi-GPU |
| - num_devices: 4 |
| - total_train_batch_size: 148 |
| - total_eval_batch_size: 148 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: linear |
| - num_epochs: 20 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | |
| |:-------------:|:-----:|:------:|:---------------:| |
| | 0.6094 | 1.0 | 7440 | 0.6185 | |
| | 0.598 | 2.0 | 14880 | 0.6124 | |
| | 0.5845 | 3.0 | 22320 | 0.6075 | |
| | 0.5723 | 4.0 | 29760 | 0.6006 | |
| | 0.5589 | 5.0 | 37200 | 0.5943 | |
| | 0.5495 | 6.0 | 44640 | 0.5894 | |
| | 0.5371 | 7.0 | 52080 | 0.5861 | |
| | 0.5291 | 8.0 | 59520 | 0.5811 | |
| | 0.52 | 9.0 | 66960 | 0.5765 | |
| | 0.5095 | 10.0 | 74400 | 0.5746 | |
| | 0.5056 | 11.0 | 81840 | 0.5700 | |
| | 0.4967 | 12.0 | 89280 | 0.5682 | |
| | 0.4894 | 13.0 | 96720 | 0.5659 | |
| | 0.4861 | 14.0 | 104160 | 0.5619 | |
| | 0.4773 | 15.0 | 111600 | 0.5599 | |
| | 0.4754 | 16.0 | 119040 | 0.5599 | |
| | 0.4689 | 17.0 | 126480 | 0.5578 | |
| | 0.4642 | 18.0 | 133920 | 0.5575 | |
| | 0.4627 | 19.0 | 141360 | 0.5566 | |
| | 0.4573 | 20.0 | 148800 | 0.5568 | |
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|
| ### Framework versions |
|
|
| - Transformers 4.33.0 |
| - Pytorch 2.1.0+cu121 |
| - Datasets 2.11.0 |
| - Tokenizers 0.13.3 |
|
|
