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+ ---
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+ base_model: OFA-Sys/chinese-clip-vit-base-patch16
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+ tags:
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+ - generated_from_trainer
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+ metrics:
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+ - accuracy
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+ model-index:
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+ - name: aoi_clip_high_resolution_text_only_gpt_new_sampler
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ [<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/shark_meow_team/huggingface/runs/gtoodtwl)
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+ # aoi_clip_high_resolution_text_only_gpt_new_sampler
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+
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+ This model is a fine-tuned version of [OFA-Sys/chinese-clip-vit-base-patch16](https://huggingface.co/OFA-Sys/chinese-clip-vit-base-patch16) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 3.2382
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+ - Accuracy: 0.1295
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 1e-05
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+ - train_batch_size: 50
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+ - eval_batch_size: 20
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+ - seed: 42
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+ - gradient_accumulation_steps: 4
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+ - total_train_batch_size: 200
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 100.0
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:-------:|:-----:|:---------------:|:--------:|
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+ | 2.5113 | 9.9839 | 3110 | 2.8518 | 0.1566 |
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+ | 2.3003 | 19.9679 | 6220 | 3.0242 | 0.1476 |
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+ | 2.2124 | 29.9518 | 9330 | 3.1246 | 0.1404 |
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+ | 2.1682 | 39.9358 | 12440 | 3.1806 | 0.1371 |
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+ | 2.1384 | 49.9197 | 15550 | 3.2024 | 0.1342 |
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+ | 2.1246 | 59.9037 | 18660 | 3.2168 | 0.1323 |
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+ | 2.1121 | 69.8876 | 21770 | 3.2209 | 0.1313 |
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+ | 2.0987 | 79.8716 | 24880 | 3.2137 | 0.1307 |
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+ | 2.0986 | 89.8555 | 27990 | 3.2374 | 0.1301 |
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+ | 2.0962 | 99.8395 | 31100 | 3.2382 | 0.1295 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.42.3
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+ - Pytorch 2.3.1+cu121
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1