gpad-v2-taskA-entropy-only-smpl
This model is a fine-tuned version of on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5692
- Accuracy: 0.74
- F1 Macro: 0.0
- F1 Weighted: 0.6294
- Precision Macro: 0.0
- Recall Macro: 0.0
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 24
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Weighted | Precision Macro | Recall Macro |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 7 | 0.6317 | 0.74 | 0.0 | 0.6294 | 0.0 | 0.0 |
| No log | 2.0 | 14 | 0.5891 | 0.74 | 0.0 | 0.6294 | 0.0 | 0.0 |
| No log | 3.0 | 21 | 0.5747 | 0.74 | 0.0 | 0.6294 | 0.0 | 0.0 |
| No log | 4.0 | 28 | 0.5692 | 0.74 | 0.0 | 0.6294 | 0.0 | 0.0 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 2.21.0
- Tokenizers 0.22.1
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