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--- |
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license: apache-2.0 |
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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: my_isl_model |
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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: train |
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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: 0.7283950617283951 |
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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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# my_isl_model |
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.9092 |
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- Accuracy: 0.7284 |
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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: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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: 0.1 |
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- num_epochs: 10 |
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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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| 3.1292 | 0.96 | 11 | 3.0256 | 0.2593 | |
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| 2.9426 | 2.0 | 23 | 2.7796 | 0.2716 | |
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| 2.706 | 2.96 | 34 | 2.5462 | 0.4321 | |
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| 2.5389 | 4.0 | 46 | 2.4454 | 0.4568 | |
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| 2.3638 | 4.96 | 57 | 2.2169 | 0.6914 | |
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| 2.1862 | 6.0 | 69 | 2.1349 | 0.6296 | |
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| 2.0459 | 6.96 | 80 | 2.1135 | 0.6049 | |
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| 1.9912 | 8.0 | 92 | 1.9757 | 0.7531 | |
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| 1.9504 | 8.96 | 103 | 1.9073 | 0.7407 | |
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| 1.942 | 9.57 | 110 | 1.9092 | 0.7284 | |
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### Framework versions |
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- Transformers 4.27.4 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.11.0 |
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- Tokenizers 0.13.3 |
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