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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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model-index: |
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- name: aoi_clip |
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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/kx6ba7ok) |
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# aoi_clip |
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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: 5.5439 |
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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: 40 |
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- eval_batch_size: 44 |
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- seed: 42 |
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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: 150.0 |
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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 | |
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|:-------------:|:-----:|:------:|:---------------:| |
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| 0.2989 | 10.0 | 14790 | 6.2126 | |
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| 0.0626 | 20.0 | 29580 | 6.1552 | |
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| 0.0467 | 30.0 | 44370 | 6.0248 | |
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| 0.0383 | 40.0 | 59160 | 6.0260 | |
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| 0.0333 | 50.0 | 73950 | 5.9856 | |
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| 0.0301 | 60.0 | 88740 | 5.8489 | |
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| 0.0275 | 70.0 | 103530 | 5.8452 | |
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| 0.0255 | 80.0 | 118320 | 5.7286 | |
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| 0.0238 | 90.0 | 133110 | 5.6773 | |
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| 0.0225 | 100.0 | 147900 | 5.5744 | |
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| 0.0243 | 110.0 | 162690 | 5.6549 | |
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| 0.024 | 120.0 | 177480 | 5.5997 | |
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| 0.0227 | 130.0 | 192270 | 5.5604 | |
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| 0.0219 | 140.0 | 207060 | 5.5429 | |
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| 0.0217 | 150.0 | 221850 | 5.5439 | |
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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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