| --- |
| 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 for Text Classification |
|
|
| This model was trained from scratch on IMDB dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.1901 |
| - Accuracy: 0.9536 |
|
|
| It achieves the following results on the evaluation set: |
| - Loss: 0.1981 |
| - Accuracy: 0.94 |
| ## Model description |
|
|
| Mamba model for text classification |
|
|
| ## 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 | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:| |
| | 0.0205 | 0.1 | 625 | 0.2462 | 0.928 | |
| | 0.671 | 0.2 | 1250 | 0.1958 | 0.9408 | |
| | 0.5961 | 0.3 | 1875 | 0.2661 | 0.9344 | |
| | 0.0167 | 0.4 | 2500 | 0.2171 | 0.9412 | |
| | 0.0007 | 0.5 | 3125 | 0.2095 | 0.9448 | |
| | 2.6807 | 0.6 | 3750 | 0.1888 | 0.9492 | |
| | 0.0155 | 0.7 | 4375 | 0.2249 | 0.95 | |
| | 0.0021 | 0.8 | 5000 | 0.1991 | 0.9528 | |
| | 0.0134 | 0.9 | 5625 | 0.1920 | 0.9524 | |
| | 0.1525 | 1.0 | 6250 | 0.1901 | 0.9536 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.40.0 |
| - Pytorch 2.2.1+cu121 |
| - Datasets 2.19.0 |
| - Tokenizers 0.19.1 |
| |
