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--- |
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library_name: transformers |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: vit_focus |
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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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# vit_focus |
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This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0604 |
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- Mse: 0.1248 |
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- Mae: 0.3083 |
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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: 5e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 32 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 30 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Mse | Mae | |
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|:-------------:|:-------:|:----:|:---------------:|:------:|:------:| |
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| No log | 1.0 | 25 | 0.0685 | 0.1397 | 0.3276 | |
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| 0.2799 | 2.0 | 50 | 0.0614 | 0.1327 | 0.3184 | |
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| 0.2799 | 3.0 | 75 | 0.0575 | 0.1317 | 0.3171 | |
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| 0.2134 | 4.0 | 100 | 0.0683 | 0.1370 | 0.3236 | |
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| 0.2018 | 5.0 | 125 | 0.0610 | 0.1353 | 0.3213 | |
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| 0.2018 | 6.0 | 150 | 0.0596 | 0.1295 | 0.3133 | |
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| 0.1714 | 7.0 | 175 | 0.0588 | 0.1327 | 0.3186 | |
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| 0.1589 | 8.0 | 200 | 0.0621 | 0.1348 | 0.3204 | |
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| 0.1589 | 9.0 | 225 | 0.0615 | 0.1306 | 0.3157 | |
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| 0.1381 | 10.0 | 250 | 0.0557 | 0.1280 | 0.3118 | |
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| 0.1381 | 11.0 | 275 | 0.0580 | 0.1311 | 0.3158 | |
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| 0.1229 | 12.0 | 300 | 0.0563 | 0.1294 | 0.3139 | |
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| 0.1112 | 13.0 | 325 | 0.0629 | 0.1393 | 0.3253 | |
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| 0.1112 | 14.0 | 350 | 0.0605 | 0.1290 | 0.3128 | |
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| 0.0999 | 15.0 | 375 | 0.0604 | 0.1248 | 0.3083 | |
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| 0.0896 | 16.0 | 400 | 0.0556 | 0.1308 | 0.3153 | |
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| 0.0896 | 17.0 | 425 | 0.0610 | 0.1347 | 0.3201 | |
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| 0.0776 | 18.0 | 450 | 0.0574 | 0.1259 | 0.3093 | |
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| 0.0776 | 19.0 | 475 | 0.0584 | 0.1253 | 0.3085 | |
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| 0.069 | 20.0 | 500 | 0.0595 | 0.1265 | 0.3097 | |
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| 0.0649 | 21.0 | 525 | 0.0576 | 0.1308 | 0.3150 | |
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| 0.0649 | 22.0 | 550 | 0.0574 | 0.1274 | 0.3109 | |
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| 0.056 | 23.0 | 575 | 0.0578 | 0.1307 | 0.3149 | |
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| 0.0508 | 24.0 | 600 | 0.0563 | 0.1296 | 0.3139 | |
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| 0.0508 | 25.0 | 625 | 0.0568 | 0.1312 | 0.3157 | |
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| 0.0468 | 26.0 | 650 | 0.0578 | 0.1287 | 0.3123 | |
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| 0.0468 | 27.0 | 675 | 0.0579 | 0.1305 | 0.3147 | |
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| 0.0432 | 28.0 | 700 | 0.0572 | 0.1301 | 0.3143 | |
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| 0.0419 | 28.8247 | 720 | 0.0580 | 0.1308 | 0.3150 | |
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### Framework versions |
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- Transformers 4.51.3 |
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- Pytorch 2.7.0 |
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- Datasets 3.5.1 |
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- Tokenizers 0.21.1 |
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