gpad-v22-taskA-entropy-only
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0287
- Accuracy: 0.9934
- F1 Macro: 0.9933
- F1 Weighted: 0.9934
- Precision Macro: 0.9948
- Recall Macro: 0.9917
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-05
- train_batch_size: 16
- eval_batch_size: 12
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Weighted | Precision Macro | Recall Macro |
|---|---|---|---|---|---|---|---|---|
| 0.0413 | 1.0 | 2736 | 0.0266 | 0.9929 | 0.9927 | 0.9929 | 0.9935 | 0.9918 |
| 0.0206 | 2.0 | 5472 | 0.0258 | 0.9935 | 0.9933 | 0.9935 | 0.9946 | 0.9920 |
| 0.0133 | 3.0 | 8208 | 0.0258 | 0.9939 | 0.9938 | 0.9939 | 0.9954 | 0.9922 |
| 0.0095 | 4.0 | 10944 | 0.0287 | 0.9934 | 0.9933 | 0.9934 | 0.9948 | 0.9917 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.8.0+cu126
- Datasets 4.3.0
- Tokenizers 0.19.1
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