Model save

README.md

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+---
+base_model: motheecreator/vit-Facial-Expression-Recognition
+tags:
+- generated_from_trainer
+datasets:
+- imagefolder
+metrics:
+- accuracy
+model-index:
+- name: vit-Facial-Expression-Recognition
+  results:
+  - task:
+      name: Image Classification
+      type: image-classification
+    dataset:
+      name: imagefolder
+      type: imagefolder
+      config: default
+      split: None
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9176650877681806
+---
+
+<!-- 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. -->
+
+# vit-Facial-Expression-Recognition
+
+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.
+It achieves the following results on the evaluation set:
+- Loss: 0.2631
+- Accuracy: 0.9177
+
+## 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: 3e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 256
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 1000
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
+|:-------------:|:------:|:----:|:---------------:|:--------:|
+| 0.5315        | 0.8909 | 100  | 0.2603          | 0.9184   |
+| 0.5202        | 1.7817 | 200  | 0.2583          | 0.9181   |
+| 0.4912        | 2.6726 | 300  | 0.2609          | 0.9171   |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

all_results.json

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+{
+    "epoch": 2.9933184855233854,
+    "eval_accuracy": 0.9176650877681806,
+    "eval_loss": 0.2630792260169983,
+    "eval_runtime": 90.3053,
+    "eval_samples_per_second": 79.486,
+    "eval_steps_per_second": 2.492
+}

config.json

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+{
+  "_name_or_path": "motheecreator/vit-Facial-Expression-Recognition",
+  "architectures": [
+    "ViTForImageClassification"
+  ],
+  "attention_probs_dropout_prob": 0.0,
+  "encoder_stride": 16,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.0,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "angry",
+    "1": "disgust",
+    "2": "fear",
+    "3": "happy",
+    "4": "neutral",
+    "5": "sad",
+    "6": "surprise"
+  },
+  "image_size": 224,
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "angry": 0,
+    "disgust": 1,
+    "fear": 2,
+    "happy": 3,
+    "neutral": 4,
+    "sad": 5,
+    "surprise": 6
+  },
+  "layer_norm_eps": 1e-12,
+  "model_type": "vit",
+  "num_attention_heads": 12,
+  "num_channels": 3,
+  "num_hidden_layers": 12,
+  "patch_size": 16,
+  "problem_type": "single_label_classification",
+  "qkv_bias": true,
+  "torch_dtype": "float32",
+  "transformers_version": "4.41.2"
+}

eval_results.json

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+{
+    "epoch": 2.9933184855233854,
+    "eval_accuracy": 0.9176650877681806,
+    "eval_loss": 0.2630792260169983,
+    "eval_runtime": 90.3053,
+    "eval_samples_per_second": 79.486,
+    "eval_steps_per_second": 2.492
+}

model.safetensors

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+version https://git-lfs.github.com/spec/v1
+oid sha256:1384b119b966d408abe2520b83cc7abf6bc219bf2422a9596d091cfffd0aaf64
+size 343239356

preprocessor_config.json

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+{
+  "_valid_processor_keys": [
+    "images",
+    "do_resize",
+    "size",
+    "resample",
+    "do_rescale",
+    "rescale_factor",
+    "do_normalize",
+    "image_mean",
+    "image_std",
+    "return_tensors",
+    "data_format",
+    "input_data_format"
+  ],
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "image_mean": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "image_processor_type": "ViTImageProcessor",
+  "image_std": [
+    0.5,
+    0.5,
+    0.5
+  ],
+  "resample": 2,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "height": 224,
+    "width": 224
+  }
+}

training_args.bin

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+size 5112