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aoi_clip_high_resolution_crossAttenttionFusion_fusin_new_sampler
sharkMeow/aoi_clip_high_resolution_crossAttenttionFusion_fusin_new_sampler
aoi_clip_high_resolution_crossAttenttionFusion_fusin_new_sampler is a machine learning model from sharkMeow. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Model type
- chinese_clip
- Access
- Public
- Created
- Oct 5, 2024
- Updated
- Oct 6, 2024
- SHA
- 71429a61
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. -->
aoi_clip_high_resolution_crossAttenttionFusion_fusin_new_sampler
This model is a fine-tuned version of OFA-Sys/chinese-clip-vit-base-patch16 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 4.5135
- Accuracy: 0.0583
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: 1e-05
- train_batch_size: 25
- eval_batch_size: 20
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 200
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 100.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 2.156 | 9.9880 | 3110 | 2.9957 | 0.0492 |
| 2.1411 | 19.9759 | 6220 | 3.0536 | 0.0537 |
| 1.9888 | 29.9639 | 9330 | 3.3324 | 0.0567 |
| 1.8759 | 39.9518 | 12440 | 3.6092 | 0.0571 |
| 1.8129 | 49.9398 | 15550 | 3.8091 | 0.0575 |
| 1.7708 | 59.9277 | 18660 | 3.9898 | 0.0578 |
| 1.7413 | 69.9157 | 21770 | 4.2735 | 0.0579 |
| 1.7172 | 79.9037 | 24880 | 4.3434 | 0.0580 |
| 1.7056 | 89.8916 | 27990 | 4.5120 | 0.0581 |
| 1.7018 | 99.8796 | 31100 | 4.5135 | 0.0582 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Type
- chinese_clip
- Created
- Oct 5, 2024
- Updated
- Oct 6, 2024