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cliplarge-ROCOv2-radiology-15ep
turing552/cliplarge-ROCOv2-radiology-15ep
cliplarge-ROCOv2-radiology-15ep is a zero-shot image classification model from turing552. Use it for the zero-shot image classification task on the model card, and read the license before you ship it in a product. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Zero-Shot Image Classification
- Library
- transformers
- Model type
- clip
- Access
- Public
- Created
- Nov 13, 2025
- Updated
- Nov 13, 2025
- SHA
- d8657c1a
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
cliplarge-ROCOv2-radiology-15ep
This model is a fine-tuned version of openai/clip-vit-large-patch14 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.7840
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: 5e-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 1.0779 | 0.3294 | 500 | 1.0447 |
| 0.8371 | 0.6588 | 1000 | 0.8224 |
| 0.7569 | 0.9881 | 1500 | 0.7495 |
| 0.5572 | 1.3175 | 2000 | 0.7123 |
| 0.5883 | 1.6469 | 2500 | 0.6588 |
| 0.5322 | 1.9763 | 3000 | 0.6107 |
| 0.3329 | 2.3057 | 3500 | 0.6131 |
| 0.3353 | 2.6350 | 4000 | 0.5954 |
| 0.3149 | 2.9644 | 4500 | 0.5589 |
| 0.1825 | 3.2938 | 5000 | 0.6371 |
| 0.2162 | 3.6232 | 5500 | 0.6013 |
| 0.215 | 3.9526 | 6000 | 0.6012 |
| 0.139 | 4.2819 | 6500 | 0.6403 |
| 0.1488 | 4.6113 | 7000 | 0.6309 |
| 0.1499 | 4.9407 | 7500 | 0.6224 |
| 0.0964 | 5.2701 | 8000 | 0.6860 |
| 0.114 | 5.5995 | 8500 | 0.6665 |
| 0.1081 | 5.9289 | 9000 | 0.6511 |
| 0.0738 | 6.2582 | 9500 | 0.7260 |
| 0.0845 | 6.5876 | 10000 | 0.6962 |
| 0.0869 | 6.9170 | 10500 | 0.6943 |
| 0.0608 | 7.2464 | 11000 | 0.7290 |
| 0.0732 | 7.5758 | 11500 | 0.7465 |
| 0.0718 | 7.9051 | 12000 | 0.7409 |
| 0.0446 | 8.2345 | 12500 | 0.7592 |
| 0.0502 | 8.5639 | 13000 | 0.7810 |
| 0.048 | 8.8933 | 13500 | 0.7845 |
| 0.0312 | 9.2227 | 14000 | 0.8026 |
| 0.0388 | 9.5520 | 14500 | 0.7967 |
| 0.0376 | 9.8814 | 15000 | 0.7953 |
| 0.0255 | 10.2108 | 15500 | 0.8029 |
| 0.0228 | 10.5402 | 16000 | 0.8011 |
| 0.0295 | 10.8696 | 16500 | 0.8137 |
| 0.0328 | 11.1989 | 17000 | 0.7920 |
| 0.0176 | 11.5283 | 17500 | 0.7832 |
| 0.0247 | 11.8577 | 18000 | 0.8009 |
| 0.0159 | 12.1871 | 18500 | 0.7912 |
| 0.023 | 12.5165 | 19000 | 0.8052 |
| 0.0234 | 12.8458 | 19500 | 0.8105 |
| 0.013 | 13.1752 | 20000 | 0.8039 |
| 0.0198 | 13.5046 | 20500 | 0.7857 |
| 0.0151 | 13.8340 | 21000 | 0.7990 |
| 0.0123 | 14.1634 | 21500 | 0.7879 |
| 0.0101 | 14.4928 | 22000 | 0.7839 |
| 0.013 | 14.8221 | 22500 | 0.7840 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.5.1+cu124
- Datasets 4.4.1
- Tokenizers 0.19.1
- Task
- Zero-Shot Image Classification
- Library
- transformers
- Type
- clip
- Created
- Nov 13, 2025
- Updated
- Nov 13, 2025