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README.md
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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_concate_fusin_crop_each_text_512
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results: []
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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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[<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/9tw3ng1k)
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# aoi_clip_high_resolution_concate_fusin_crop_each_text_512
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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: 3.5539
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- Accuracy: 0.0669
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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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: 15
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- eval_batch_size: 20
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- seed: 42
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- gradient_accumulation_steps: 14
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- total_train_batch_size: 210
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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: 60.0
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- mixed_precision_training: Native AMP
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|
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| 1.5814 | 6.0 | 1530 | 3.0257 | 0.0726 |
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| 1.4807 | 12.0 | 3060 | 3.2677 | 0.0712 |
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| 1.4075 | 18.0 | 4590 | 3.3332 | 0.0703 |
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| 1.3618 | 24.0 | 6120 | 3.2491 | 0.0692 |
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| 1.3396 | 30.0 | 7650 | 3.3756 | 0.0690 |
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| 1.3298 | 36.0 | 9180 | 3.5386 | 0.0678 |
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| 1.324 | 42.0 | 10710 | 3.5245 | 0.0675 |
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| 1.3177 | 48.0 | 12240 | 3.5136 | 0.0671 |
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| 1.3181 | 54.0 | 13770 | 3.4984 | 0.0669 |
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| 1.3117 | 60.0 | 15300 | 3.5539 | 0.0669 |
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### Framework versions
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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
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