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--- |
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license: apache-2.0 |
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base_model: google/vit-base-patch16-224-in21k |
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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: rgai_emotion_recognition |
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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: 0.58125 |
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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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# rgai_emotion_recognition |
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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: 1.3077 |
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- Accuracy: 0.5813 |
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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: 2e-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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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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: 15 |
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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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| 2.0698 | 1.0 | 25 | 2.0921 | 0.1125 | |
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| 1.973 | 2.0 | 50 | 1.9930 | 0.1938 | |
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| 1.8091 | 3.0 | 75 | 1.8374 | 0.3937 | |
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| 1.5732 | 4.0 | 100 | 1.6804 | 0.475 | |
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| 1.4087 | 5.0 | 125 | 1.5660 | 0.5125 | |
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| 1.2653 | 6.0 | 150 | 1.4769 | 0.5375 | |
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| 1.1443 | 7.0 | 175 | 1.4084 | 0.55 | |
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| 0.9888 | 8.0 | 200 | 1.3633 | 0.5625 | |
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| 0.9029 | 9.0 | 225 | 1.3305 | 0.55 | |
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| 0.8372 | 10.0 | 250 | 1.3077 | 0.5813 | |
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| 0.7569 | 11.0 | 275 | 1.2983 | 0.5625 | |
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| 0.6886 | 12.0 | 300 | 1.2806 | 0.5687 | |
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| 0.6216 | 13.0 | 325 | 1.2718 | 0.5687 | |
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| 0.6385 | 14.0 | 350 | 1.2700 | 0.5563 | |
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| 0.6029 | 15.0 | 375 | 1.2693 | 0.5625 | |
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### Framework versions |
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- Transformers 4.33.2 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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