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visual_emotion_classification_vit_base_finetunned

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  1. README.md +36 -16
  2. model.safetensors +1 -1
  3. runs/Feb11_13-28-21_7cbe7798dc4c/events.out.tfevents.1707659099.7cbe7798dc4c.1515.1 +3 -0
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: 0.51875
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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 [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: 1.3160
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- - Accuracy: 0.5188
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  ## Model description
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@@ -52,33 +52,53 @@ More information needed
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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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  - 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 | 40 | 1.8770 | 0.3812 |
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- | No log | 2.0 | 80 | 1.6143 | 0.45 |
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- | No log | 3.0 | 120 | 1.5482 | 0.425 |
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- | No log | 4.0 | 160 | 1.4722 | 0.4625 |
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- | No log | 5.0 | 200 | 1.4074 | 0.5 |
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- | No log | 6.0 | 240 | 1.3503 | 0.5125 |
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- | No log | 7.0 | 280 | 1.3016 | 0.5687 |
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- | No log | 8.0 | 320 | 1.3337 | 0.5188 |
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- | No log | 9.0 | 360 | 1.3364 | 0.5188 |
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- | No log | 10.0 | 400 | 1.3169 | 0.5188 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ### Framework versions
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  - Transformers 4.35.2
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  - Pytorch 2.1.0+cu121
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- - Datasets 2.16.1
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  - Tokenizers 0.15.1
 
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  metrics:
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  - name: Accuracy
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  type: accuracy
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+ value: 0.5125
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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 [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: 1.3576
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+ - Accuracy: 0.5125
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  ## Model description
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  ### Training hyperparameters
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  The following hyperparameters were used during training:
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+ - learning_rate: 2.5e-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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  - 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: 30
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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 | 40 | 1.9700 | 0.2625 |
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+ | 2.0074 | 2.0 | 80 | 1.7194 | 0.3688 |
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+ | 1.726 | 3.0 | 120 | 1.5775 | 0.3875 |
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+ | 1.5202 | 4.0 | 160 | 1.4900 | 0.4875 |
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+ | 1.3857 | 5.0 | 200 | 1.4261 | 0.4938 |
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+ | 1.3857 | 6.0 | 240 | 1.4090 | 0.5 |
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+ | 1.2831 | 7.0 | 280 | 1.3510 | 0.475 |
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+ | 1.2007 | 8.0 | 320 | 1.3788 | 0.475 |
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+ | 1.1256 | 9.0 | 360 | 1.3183 | 0.5 |
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+ | 1.0345 | 10.0 | 400 | 1.2937 | 0.4813 |
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+ | 1.0345 | 11.0 | 440 | 1.2384 | 0.5437 |
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+ | 0.9438 | 12.0 | 480 | 1.2100 | 0.525 |
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+ | 0.872 | 13.0 | 520 | 1.2450 | 0.525 |
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+ | 0.8193 | 14.0 | 560 | 1.2264 | 0.5312 |
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+ | 0.763 | 15.0 | 600 | 1.2296 | 0.5125 |
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+ | 0.763 | 16.0 | 640 | 1.2539 | 0.5188 |
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+ | 0.7166 | 17.0 | 680 | 1.2253 | 0.5563 |
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+ | 0.6328 | 18.0 | 720 | 1.2723 | 0.5312 |
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+ | 0.5917 | 19.0 | 760 | 1.2870 | 0.4875 |
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+ | 0.5841 | 20.0 | 800 | 1.3011 | 0.5375 |
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+ | 0.5841 | 21.0 | 840 | 1.2071 | 0.575 |
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+ | 0.559 | 22.0 | 880 | 1.2555 | 0.575 |
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+ | 0.5109 | 23.0 | 920 | 1.3140 | 0.5 |
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+ | 0.5036 | 24.0 | 960 | 1.2593 | 0.5 |
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+ | 0.4787 | 25.0 | 1000 | 1.2573 | 0.5813 |
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+ | 0.4787 | 26.0 | 1040 | 1.2163 | 0.55 |
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+ | 0.4583 | 27.0 | 1080 | 1.2349 | 0.5563 |
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+ | 0.4766 | 28.0 | 1120 | 1.3349 | 0.5188 |
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+ | 0.4709 | 29.0 | 1160 | 1.3284 | 0.5312 |
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+ | 0.4442 | 30.0 | 1200 | 1.2684 | 0.5625 |
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  ### Framework versions
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  - Transformers 4.35.2
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  - Pytorch 2.1.0+cu121
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+ - Datasets 2.17.0
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  - Tokenizers 0.15.1
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