rgai_emotion_recognition

README.md

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+---
+license: apache-2.0
+base_model: google/vit-base-patch16-224-in21k
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: rgai_emotion_recognition
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.58125
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# rgai_emotion_recognition
+
+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.
+It achieves the following results on the evaluation set:
+- Loss: 1.3077
+- Accuracy: 0.5813
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 128
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 15
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 2.0698        | 1.0   | 25   | 2.0921          | 0.1125   |
+| 1.973         | 2.0   | 50   | 1.9930          | 0.1938   |
+| 1.8091        | 3.0   | 75   | 1.8374          | 0.3937   |
+| 1.5732        | 4.0   | 100  | 1.6804          | 0.475    |
+| 1.4087        | 5.0   | 125  | 1.5660          | 0.5125   |
+| 1.2653        | 6.0   | 150  | 1.4769          | 0.5375   |
+| 1.1443        | 7.0   | 175  | 1.4084          | 0.55     |
+| 0.9888        | 8.0   | 200  | 1.3633          | 0.5625   |
+| 0.9029        | 9.0   | 225  | 1.3305          | 0.55     |
+| 0.8372        | 10.0  | 250  | 1.3077          | 0.5813   |
+| 0.7569        | 11.0  | 275  | 1.2983          | 0.5625   |
+| 0.6886        | 12.0  | 300  | 1.2806          | 0.5687   |
+| 0.6216        | 13.0  | 325  | 1.2718          | 0.5687   |
+| 0.6385        | 14.0  | 350  | 1.2700          | 0.5563   |
+| 0.6029        | 15.0  | 375  | 1.2693          | 0.5625   |
+
+
+### Framework versions
+
+- Transformers 4.33.2
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.13.3

pytorch_model.bin

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