wise-cosmos-218
This model is a fine-tuned version of facebook/convnextv2-tiny-1k-224 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5895
- Accuracy: 0.6328
- Precision: 0.6756
- Recall: 0.6328
- F1: 0.6413
- Roc Auc: 0.8748
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: 0.0001
- train_batch_size: 256
- eval_batch_size: 256
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Roc Auc |
|---|---|---|---|---|---|---|---|---|
| 1.3576 | 1.0 | 17 | 1.2560 | 0.2383 | 0.4653 | 0.2383 | 0.3033 | 0.7652 |
| 1.0327 | 2.0 | 34 | 0.8853 | 0.5326 | 0.5906 | 0.5326 | 0.5534 | 0.8194 |
| 0.764 | 3.0 | 51 | 0.6813 | 0.6159 | 0.6415 | 0.6159 | 0.6239 | 0.8545 |
| 0.6357 | 4.0 | 68 | 0.6066 | 0.6367 | 0.6764 | 0.6367 | 0.6464 | 0.8702 |
| 0.5797 | 5.0 | 85 | 0.5895 | 0.6328 | 0.6756 | 0.6328 | 0.6413 | 0.8748 |
Framework versions
- Transformers 4.52.3
- Pytorch 2.7.0+cpu
- Datasets 3.6.0
- Tokenizers 0.21.0