lbl-file14-fold3
This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3738
- Accuracy: 0.8897
- F1: 0.8852
- Precision: 0.8946
- Recall: 0.8897
- Accuracy Label Label 0: 0.7763
- Accuracy Label Label 1: 0.568
- Accuracy Label Label 2: 0.6768
- Accuracy Label Label 3: 0.9388
- Accuracy Label Label 4: 0.7632
- Accuracy Label Label 5: 0.9618
- Accuracy Label Label 6: 0.9765
- Accuracy Label Label 7: 0.9731
- Accuracy Label Label 8: 0.9903
- Accuracy Label Label 9: 1.0
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: 4e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | Accuracy Label Label 0 | Accuracy Label Label 1 | Accuracy Label Label 2 | Accuracy Label Label 3 | Accuracy Label Label 4 | Accuracy Label Label 5 | Accuracy Label Label 6 | Accuracy Label Label 7 | Accuracy Label Label 8 | Accuracy Label Label 9 |
|---|
| No log | 0.5 | 50 | 0.3928 | 0.8834 | 0.8824 | 0.8912 | 0.8834 | 0.8026 | 0.64 | 0.7273 | 0.9235 | 0.7632 | 0.8702 | 0.9647 | 0.9327 | 1.0 | 0.9891 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.13.3
