VIT-fineTuned
Browse files- README.md +71 -0
- model.safetensors +1 -1
README.md
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---
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base_model: VIT
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tags:
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- image-classification
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- breast cancer
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- generated_from_trainer
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metrics:
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- accuracy
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- precision
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- recall
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- f1
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model-index:
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- name: vit
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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
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This model is a fine-tuned version of [VIT](https://huggingface.co/VIT) on the Mammogram V1 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1157
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- Accuracy: 0.9625
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- Precision: 0.9745
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- Recall: 0.9625
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- F1: 0.9682
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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: 32
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- eval_batch_size: 32
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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: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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| 0.4204 | 1.0 | 1112 | 0.1572 | 0.9797 | 0.9740 | 0.9797 | 0.9767 |
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| 0.3987 | 2.0 | 2224 | 0.2308 | 0.9253 | 0.9745 | 0.9253 | 0.9482 |
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| 0.2347 | 3.0 | 3336 | 0.1360 | 0.9516 | 0.9737 | 0.9516 | 0.9622 |
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| 0.1283 | 4.0 | 4448 | 0.1255 | 0.9564 | 0.9743 | 0.9564 | 0.9649 |
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| 0.1304 | 5.0 | 5560 | 0.1157 | 0.9625 | 0.9745 | 0.9625 | 0.9682 |
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### Framework versions
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- Transformers 4.42.4
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- Pytorch 2.3.1+cu121
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- Datasets 2.21.0
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- Tokenizers 0.19.1
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model.safetensors
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version https://git-lfs.github.com/spec/v1
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-
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size 343223968
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version https://git-lfs.github.com/spec/v1
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size 343223968
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