lbl-file17-fold2
This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.8894
- Accuracy: 0.4357
- F1: 0.3752
- Precision: 0.5921
- Recall: 0.4357
- Accuracy Label Label 0: 0.0142
- Accuracy Label Label 1: 0.0153
- Accuracy Label Label 2: 0.0351
- Accuracy Label Label 3: 0.1468
- Accuracy Label Label 4: 0.0021
- Accuracy Label Label 5: 0.1632
- Accuracy Label Label 6: 0.2124
- Accuracy Label Label 7: 0.4376
- Accuracy Label Label 8: 0.2038
- Accuracy Label Label 9: 0.9317
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: 2e-07
- 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 | 0.31 | 250 | 1.8642 | 0.4331 | 0.3765 | 0.5576 | 0.4331 | 0.0237 | 0.0153 | 0.05 | 0.2 | 0.0021 | 0.1656 | 0.2314 | 0.4156 | 0.2092 | 0.9300 |
| No log | 0.61 | 500 | 1.8862 | 0.4347 | 0.3749 | 0.5722 | 0.4347 | 0.0142 | 0.0153 | 0.0362 | 0.1597 | 0.0021 | 0.1617 | 0.2155 | 0.4315 | 0.2065 | 0.9325 |
| No log | 0.92 | 750 | 1.8894 | 0.4357 | 0.3752 | 0.5921 | 0.4357 | 0.0142 | 0.0153 | 0.0351 | 0.1468 | 0.0021 | 0.1632 | 0.2124 | 0.4376 | 0.2038 | 0.9317 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.13.3
