medsiglip-448-cied-650-binary-classification
This model is a fine-tuned version of google/medsiglip-448 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.7149
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: 0.001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- 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: cosine
- lr_scheduler_warmup_steps: 5
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 7.3163 | 1.0 | 5 | 8.6896 |
| 5.8702 | 2.0 | 10 | 3.7810 |
| 4.3275 | 3.0 | 15 | 3.9249 |
| 3.7694 | 4.0 | 20 | 3.7549 |
| 3.7601 | 5.0 | 25 | 3.7149 |
| 3.7215 | 6.0 | 30 | 3.7158 |
| 3.7119 | 7.0 | 35 | 3.7149 |
| 3.7088 | 8.0 | 40 | 3.7150 |
| 3.7067 | 9.0 | 45 | 3.7159 |
| 3.703 | 10.0 | 50 | 3.7149 |
| 3.7032 | 11.0 | 55 | 3.7150 |
| 3.7017 | 12.0 | 60 | 3.7149 |
| 3.7019 | 13.0 | 65 | 3.7149 |
| 3.7014 | 14.0 | 70 | 3.7149 |
| 3.7012 | 15.0 | 75 | 3.7149 |
Framework versions
- Transformers 4.57.3
- Pytorch 2.9.0+cu126
- Datasets 4.4.2
- Tokenizers 0.22.1
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Base model
google/medsiglip-448