mamba2_130m_multi_label_classification
This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1412
- Flat Accuracy: 0.9617
- Accuracy: 0.7177
- Precision: 0.8407
- Recall: 0.8833
- F1 Score: 0.8615
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: 12
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Flat Accuracy | Accuracy | Precision | Recall | F1 Score |
|---|
| 0.1343 | 1.0 | 1667 | 0.1075 | 0.9621 | 0.7243 | 0.8606 | 0.8579 | 0.8592 |
| 0.0783 | 2.0 | 3334 | 0.1110 | 0.9610 | 0.7129 | 0.8342 | 0.8874 | 0.8600 |
| 0.0233 | 3.0 | 5001 | 0.1305 | 0.9594 | 0.7031 | 0.8263 | 0.8854 | 0.8548 |
| 0.0055 | 4.0 | 6668 | 0.1398 | 0.9605 | 0.7072 | 0.8300 | 0.8895 | 0.8588 |
| 0.0022 | 5.0 | 8335 | 0.1412 | 0.9617 | 0.7177 | 0.8407 | 0.8833 | 0.8615 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.1.1+cu118
- Datasets 3.1.0
- Tokenizers 0.19.1
