| --- |
| library_name: transformers |
| license: mit |
| base_model: microsoft/deberta-v3-base |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: deberta-v3-base_smcalflow_balanced-classifier |
| 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. --> |
|
|
| # deberta-v3-base_smcalflow_balanced-classifier |
|
|
| This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.0390 |
| - F1 Micro: 0.8614 |
| - F1 Macro: 0.1143 |
| - Exact Match: 0.125 |
|
|
| ## Model description |
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| More information needed |
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| ## Intended uses & limitations |
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| More information needed |
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| ## Training and evaluation data |
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| More information needed |
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| ## Training procedure |
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| ### Training hyperparameters |
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| The following hyperparameters were used during training: |
| - learning_rate: 2e-05 |
| - train_batch_size: 32 |
| - 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: 5 |
|
|
| ### Training results |
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|
| | Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | Exact Match | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:-----------:| |
| | 0.0858 | 1.0 | 656 | 0.0804 | 0.6547 | 0.0284 | 0.0 | |
| | 0.0637 | 2.0 | 1312 | 0.0592 | 0.7628 | 0.0588 | 0.0056 | |
| | 0.0480 | 3.0 | 1968 | 0.0460 | 0.8277 | 0.0931 | 0.0458 | |
| | 0.0426 | 4.0 | 2624 | 0.0408 | 0.8548 | 0.1109 | 0.125 | |
| | 0.0405 | 5.0 | 3280 | 0.0390 | 0.8614 | 0.1143 | 0.125 | |
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| ### Framework versions |
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| - Transformers 5.2.0 |
| - Pytorch 2.10.0+cu128 |
| - Datasets 4.5.0 |
| - Tokenizers 0.22.2 |
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|
