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NekoJar
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trainer_output

Image Classification
Transformers
Safetensors
vit
Generated from Trainer
Eval Results (legacy)
Model card Files
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NekoJar commited on
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End of training

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Files changed (3) hide show
  1. README.md +8 -8
  2. all_results.json +6 -6
  3. eval_results.json +6 -6
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: 0.8617000955109838
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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 [motheecreator/vit-Facial-Expression-Recognition](https://huggingface.co/motheecreator/vit-Facial-Expression-Recognition) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.3968
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- - Accuracy: 0.8617
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  ## Model description
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@@ -65,11 +65,11 @@ The following hyperparameters were used during training:
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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 | 41 | 0.4036 | 0.8564 |
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- | 0.5372 | 2.0 | 82 | 0.3990 | 0.8586 |
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- | 0.5297 | 3.0 | 123 | 0.3968 | 0.8617 |
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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: 0.6458943019452573
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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 [motheecreator/vit-Facial-Expression-Recognition](https://huggingface.co/motheecreator/vit-Facial-Expression-Recognition) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 1.6672
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+ - Accuracy: 0.6459
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  ## Model description
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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 | 0.9890 | 45 | 2.0266 | 0.2080 |
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+ | 2.0636 | 1.9890 | 90 | 1.9071 | 0.5510 |
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+ | 1.9588 | 2.9890 | 135 | 1.6672 | 0.6459 |
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  ### Framework versions
all_results.json CHANGED
@@ -1,8 +1,8 @@
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  {
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- "epoch": 3.0,
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- "eval_accuracy": 0.8617000955109838,
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- "eval_loss": 0.39679861068725586,
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- "eval_runtime": 48.3954,
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- "eval_samples_per_second": 108.171,
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- "eval_steps_per_second": 1.694
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  }
 
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  {
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+ "epoch": 2.989010989010989,
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+ "eval_accuracy": 0.6458943019452573,
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+ "eval_loss": 1.6671953201293945,
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+ "eval_runtime": 55.3025,
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+ "eval_samples_per_second": 105.04,
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+ "eval_steps_per_second": 1.645
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  }
eval_results.json CHANGED
@@ -1,8 +1,8 @@
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  {
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- "epoch": 3.0,
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- "eval_accuracy": 0.8617000955109838,
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- "eval_loss": 0.39679861068725586,
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- "eval_runtime": 48.3954,
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- "eval_samples_per_second": 108.171,
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- "eval_steps_per_second": 1.694
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  }
 
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  {
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+ "epoch": 2.989010989010989,
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+ "eval_accuracy": 0.6458943019452573,
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+ "eval_loss": 1.6671953201293945,
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+ "eval_runtime": 55.3025,
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+ "eval_samples_per_second": 105.04,
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+ "eval_steps_per_second": 1.645
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  }