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--- |
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library_name: transformers |
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base_model: Melo1512/vit-msn-small-beta-fia-manually-enhanced-HSV_test_2 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- imagefolder |
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metrics: |
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- accuracy |
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model-index: |
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- name: vit-msn-small-beta-fia-manually-enhanced-HSV_test_3 |
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results: |
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- task: |
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name: Image Classification |
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type: image-classification |
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dataset: |
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name: imagefolder |
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type: imagefolder |
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config: default |
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split: test |
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args: default |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8661971830985915 |
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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-msn-small-beta-fia-manually-enhanced-HSV_test_3 |
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This model is a fine-tuned version of [Melo1512/vit-msn-small-beta-fia-manually-enhanced-HSV_test_2](https://huggingface.co/Melo1512/vit-msn-small-beta-fia-manually-enhanced-HSV_test_2) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5321 |
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- Accuracy: 0.8662 |
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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: 64 |
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- eval_batch_size: 64 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 256 |
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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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- lr_scheduler_warmup_ratio: 0.33 |
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- num_epochs: 50 |
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- label_smoothing_factor: 0.1 |
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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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| No log | 0.5714 | 1 | 0.5167 | 0.8803 | |
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| No log | 1.7143 | 3 | 0.5197 | 0.8803 | |
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| No log | 2.8571 | 5 | 0.5266 | 0.8803 | |
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| No log | 4.0 | 7 | 0.5391 | 0.8803 | |
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| No log | 4.5714 | 8 | 0.5425 | 0.8803 | |
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| 0.4435 | 5.7143 | 10 | 0.5403 | 0.8803 | |
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| 0.4435 | 6.8571 | 12 | 0.5251 | 0.8803 | |
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| 0.4435 | 8.0 | 14 | 0.5160 | 0.8732 | |
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| 0.4435 | 8.5714 | 15 | 0.5123 | 0.8873 | |
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| 0.4435 | 9.7143 | 17 | 0.5292 | 0.8803 | |
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| 0.4435 | 10.8571 | 19 | 0.5686 | 0.8732 | |
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| 0.4418 | 12.0 | 21 | 0.5460 | 0.8732 | |
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| 0.4418 | 12.5714 | 22 | 0.5333 | 0.8873 | |
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| 0.4418 | 13.7143 | 24 | 0.5152 | 0.8803 | |
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| 0.4418 | 14.8571 | 26 | 0.5236 | 0.8732 | |
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| 0.4418 | 16.0 | 28 | 0.5372 | 0.8592 | |
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| 0.4418 | 16.5714 | 29 | 0.5472 | 0.8592 | |
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| 0.4363 | 17.7143 | 31 | 0.5422 | 0.8592 | |
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| 0.4363 | 18.8571 | 33 | 0.5293 | 0.8803 | |
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| 0.4363 | 20.0 | 35 | 0.5235 | 0.8803 | |
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| 0.4363 | 20.5714 | 36 | 0.5240 | 0.8803 | |
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| 0.4363 | 21.7143 | 38 | 0.5302 | 0.8803 | |
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| 0.4371 | 22.8571 | 40 | 0.5324 | 0.8803 | |
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| 0.4371 | 24.0 | 42 | 0.5349 | 0.8803 | |
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| 0.4371 | 24.5714 | 43 | 0.5363 | 0.8732 | |
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| 0.4371 | 25.7143 | 45 | 0.5342 | 0.8732 | |
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| 0.4371 | 26.8571 | 47 | 0.5315 | 0.8732 | |
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| 0.4371 | 28.0 | 49 | 0.5319 | 0.8732 | |
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| 0.4298 | 28.5714 | 50 | 0.5321 | 0.8662 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.2.0 |
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- Tokenizers 0.19.1 |
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