| --- |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: mamba_text_classification |
| 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. --> |
|
|
| # mamba_text_classification |
|
|
| This model was trained from scratch on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.6382 |
| - Accuracy: 0.7623 |
|
|
| ## Model description |
|
|
| More information needed |
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|
| ## Intended uses & limitations |
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| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
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|
| ### Training hyperparameters |
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|
| The following hyperparameters were used during training: |
| - learning_rate: 5e-05 |
| - train_batch_size: 4 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - gradient_accumulation_steps: 32 |
| - total_train_batch_size: 128 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_ratio: 0.01 |
| - num_epochs: 2 |
|
|
| ### Training results |
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|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 0.7591 | 0.2 | 33 | 0.7658 | 0.65 | |
| | 0.7317 | 0.4 | 66 | 0.7151 | 0.6915 | |
| | 0.7107 | 0.6 | 99 | 0.6968 | 0.7019 | |
| | 0.6619 | 0.8 | 132 | 0.6756 | 0.7226 | |
| | 0.5397 | 1.0 | 165 | 0.6713 | 0.7368 | |
| | 0.7309 | 1.19 | 198 | 0.6560 | 0.7519 | |
| | 0.6181 | 1.39 | 231 | 0.6413 | 0.7519 | |
| | 0.6762 | 1.59 | 264 | 0.6399 | 0.7566 | |
| | 0.5834 | 1.79 | 297 | 0.6375 | 0.7613 | |
| | 0.5753 | 1.99 | 330 | 0.6382 | 0.7623 | |
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| ### Framework versions |
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|
| - Transformers 4.38.2 |
| - Pytorch 2.2.1+cu121 |
| - Datasets 2.18.0 |
| - Tokenizers 0.15.2 |
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|
