---
library_name: transformers
base_model: openai/clip-vit-large-patch14
tags:
- generated_from_trainer
model-index:
- name: cliplarge-ROCOv2-radiology-15ep
  results: []
---

<!-- 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](https://huggingface.co/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