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mhdiqbalpradipta
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emotion_classification

Image Classification
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  1. README.md +14 -7
  2. model.safetensors +1 -1
  3. runs/Feb11_03-41-52_e9246a0f957f/events.out.tfevents.1707622913.e9246a0f957f.2231.0 +2 -2
README.md CHANGED
@@ -22,7 +22,7 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.65625
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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
@@ -32,8 +32,8 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [dennisjooo/emotion_classification](https://huggingface.co/dennisjooo/emotion_classification) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.3030
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- - Accuracy: 0.6562
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  ## Model description
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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: cosine_with_restarts
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- - num_epochs: 3
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  - mixed_precision_training: Native AMP
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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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- | 0.058 | 1.0 | 40 | 1.7427 | 0.5312 |
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- | 0.0656 | 2.0 | 80 | 1.5938 | 0.5687 |
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- | 0.1325 | 3.0 | 120 | 1.3030 | 0.6562 |
 
 
 
 
 
 
 
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  ### Framework versions
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.7575
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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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  This model is a fine-tuned version of [dennisjooo/emotion_classification](https://huggingface.co/dennisjooo/emotion_classification) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.7891
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+ - Accuracy: 0.7575
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  ## Model description
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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: cosine_with_restarts
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+ - num_epochs: 10
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  - mixed_precision_training: Native AMP
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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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+ | 0.7123 | 1.0 | 25 | 0.8681 | 0.735 |
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+ | 0.6349 | 2.0 | 50 | 0.8721 | 0.73 |
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+ | 0.6354 | 3.0 | 75 | 0.8732 | 0.725 |
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+ | 0.6189 | 4.0 | 100 | 0.8406 | 0.735 |
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+ | 0.6364 | 5.0 | 125 | 0.8456 | 0.74 |
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+ | 0.5833 | 6.0 | 150 | 0.8503 | 0.725 |
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+ | 0.5384 | 7.0 | 175 | 0.8023 | 0.755 |
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+ | 0.5297 | 8.0 | 200 | 0.8002 | 0.7525 |
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+ | 0.5487 | 9.0 | 225 | 0.8253 | 0.745 |
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+ | 0.5068 | 10.0 | 250 | 0.7891 | 0.7575 |
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  ### Framework versions
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