aoi_clip_high_resolution_crossAttenttionFusion_fusin_gpt_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: 5.3131
- Accuracy: 0.0559
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: 200.0
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
2.152 | 19.9759 | 6220 | 3.0212 | 0.0537 |
1.9424 | 39.9518 | 12440 | 3.4495 | 0.0563 |
1.7646 | 59.9277 | 18660 | 3.9469 | 0.0561 |
1.6901 | 79.9037 | 24880 | 4.2354 | 0.0550 |
1.6562 | 99.8796 | 31100 | 4.6732 | 0.0548 |
1.6398 | 119.8555 | 37320 | 4.8612 | 0.0550 |
1.6289 | 139.8314 | 43540 | 4.8784 | 0.0550 |
1.6192 | 159.8073 | 49760 | 5.2516 | 0.0554 |
1.6163 | 179.7832 | 55980 | 5.2837 | 0.0558 |
1.6165 | 199.7591 | 62200 | 5.3131 | 0.0558 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for sharkMeow/aoi_clip_high_resolution_crossAttenttionFusion_fusin_gpt_new_sampler
Base model
OFA-Sys/chinese-clip-vit-base-patch16