| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: microsoft/unixcoder-base |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: my-unixcoder-RQ3 |
| 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. --> |
|
|
| # my-unixcoder-RQ3 |
|
|
| This model is a fine-tuned version of [microsoft/unixcoder-base](https://huggingface.co/microsoft/unixcoder-base) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.5170 |
| - Accuracy: 0.9459 |
| - F1 Macro: 0.6581 |
| - F1 Weighted: 0.9465 |
|
|
| ## 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: 1e-05 |
| - train_batch_size: 64 |
| - eval_batch_size: 64 |
| - seed: 42 |
| - 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: linear |
| - lr_scheduler_warmup_steps: 0.1 |
| - num_epochs: 10 |
| - mixed_precision_training: Native AMP |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Weighted | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:| |
| | 0.4074 | 1.0 | 539 | 0.4512 | 0.9250 | 0.2726 | 0.9164 | |
| | 0.3457 | 2.0 | 1078 | 0.3373 | 0.9445 | 0.5980 | 0.9414 | |
| | 0.2816 | 3.0 | 1617 | 0.3155 | 0.9452 | 0.6540 | 0.9452 | |
| | 0.2311 | 4.0 | 2156 | 0.3363 | 0.9459 | 0.6412 | 0.9453 | |
| | 0.1854 | 5.0 | 2695 | 0.3757 | 0.9445 | 0.6623 | 0.9460 | |
| | 0.1534 | 6.0 | 3234 | 0.4139 | 0.9464 | 0.6674 | 0.9473 | |
| | 0.1155 | 7.0 | 3773 | 0.4640 | 0.9457 | 0.6627 | 0.9468 | |
| | 0.1087 | 8.0 | 4312 | 0.4969 | 0.9448 | 0.6585 | 0.9457 | |
| | 0.0807 | 9.0 | 4851 | 0.5103 | 0.9457 | 0.6551 | 0.9461 | |
| | 0.0726 | 10.0 | 5390 | 0.5170 | 0.9459 | 0.6581 | 0.9465 | |
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|
| ### Framework versions |
|
|
| - Transformers 5.0.0 |
| - Pytorch 2.10.0+cu128 |
| - Datasets 4.8.3 |
| - Tokenizers 0.22.2 |
|
|
