update model card README.md
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README.md
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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: emotion_classification
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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: 0.3
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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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# emotion_classification
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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: 1.9455
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- Accuracy: 0.3
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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: 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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- 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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| No log | 1.0 | 10 | 2.0636 | 0.1187 |
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| No log | 2.0 | 20 | 2.0568 | 0.1437 |
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| No log | 3.0 | 30 | 2.0321 | 0.1812 |
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| No log | 4.0 | 40 | 2.0247 | 0.2 |
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| No log | 5.0 | 50 | 1.9975 | 0.3125 |
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| No log | 6.0 | 60 | 1.9793 | 0.2875 |
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| No log | 7.0 | 70 | 1.9746 | 0.275 |
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| No log | 8.0 | 80 | 1.9530 | 0.3063 |
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| No log | 9.0 | 90 | 1.9487 | 0.3438 |
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| No log | 10.0 | 100 | 1.9513 | 0.2812 |
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### Framework versions
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- Transformers 4.28.0
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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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