| | --- |
| | 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 an unknown dataset. |
| | It achieves the following results on the evaluation set: |
| | - Loss: 0.2354 |
| | - Accuracy: 0.9448 |
| |
|
| | ## 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: 5e-05 |
| | - train_batch_size: 4 |
| | - eval_batch_size: 16 |
| | - seed: 42 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: cosine |
| | - lr_scheduler_warmup_ratio: 0.01 |
| | - num_epochs: 1 |
| | |
| | ### Training results |
| | |
| | | Training Loss | Epoch | Step | Validation Loss | Accuracy | |
| | |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | | 0.0005 | 0.1 | 625 | 0.5217 | 0.9106 | |
| | | 2.0869 | 0.2 | 1250 | 0.2894 | 0.9134 | |
| | | 0.0191 | 0.3 | 1875 | 0.3094 | 0.9346 | |
| | | 0.0078 | 0.4 | 2500 | 0.2280 | 0.9394 | |
| | | 0.0002 | 0.5 | 3125 | 0.2279 | 0.9426 | |
| | | 2.5961 | 0.6 | 3750 | 0.2347 | 0.945 | |
| | | 0.1269 | 0.7 | 4375 | 0.2487 | 0.9422 | |
| | | 0.001 | 0.8 | 5000 | 0.2367 | 0.9454 | |
| | | 0.0069 | 0.9 | 5625 | 0.2351 | 0.9454 | |
| | | 0.6904 | 1.0 | 6250 | 0.2354 | 0.9448 | |
| | |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.41.2 |
| | - Pytorch 2.3.0+cu121 |
| | - Datasets 2.19.2 |
| | - Tokenizers 0.19.1 |
| | |
