lbl-file1-fold4
This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2108
- Accuracy: 0.5932
- F1: 0.5892
- Precision: 0.5957
- Recall: 0.5932
- Accuracy Label Label 0: 0.7851
- Accuracy Label Label 1: 0.6081
- Accuracy Label Label 2: 0.5992
- Accuracy Label Label 3: 0.7510
- Accuracy Label Label 4: 0.7115
- Accuracy Label Label 5: 0.4390
- Accuracy Label Label 6: 0.7063
- Accuracy Label Label 7: 0.3385
- Accuracy Label Label 8: 0.5880
- Accuracy Label Label 9: 0.4050
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: 1e-06
- 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 |
|---|
| 1.256 | 0.64 | 100 | 1.2135 | 0.592 | 0.5876 | 0.5945 | 0.592 | 0.7934 | 0.6081 | 0.5992 | 0.7510 | 0.7115 | 0.4350 | 0.7100 | 0.3308 | 0.5794 | 0.4008 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.13.3
