End of training

README.md

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+---
+base_model: motheecreator/vit-Facial-Expression-Recognition
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: vit-Facial-Expression-Recognitio
+  results: []
+---
+
+<!-- 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-Recognitio
+
+This model is a fine-tuned version of [motheecreator/vit-Facial-Expression-Recognition](https://huggingface.co/motheecreator/vit-Facial-Expression-Recognition) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3936
+- Accuracy: 0.8675
+
+## 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: 64
+- eval_batch_size: 64
+- seed: 42
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 512
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.5969        | 0.34  | 100  | 0.3997          | 0.8652   |
+| 0.609         | 0.67  | 200  | 0.3994          | 0.8644   |
+| 0.6038        | 1.01  | 300  | 0.3969          | 0.8677   |
+| 0.5819        | 1.35  | 400  | 0.3947          | 0.8674   |
+| 0.5864        | 1.69  | 500  | 0.3936          | 0.8675   |
+| 0.5819        | 2.02  | 600  | 0.3925          | 0.8661   |
+| 0.5694        | 2.36  | 700  | 0.3961          | 0.8656   |
+| 0.5618        | 2.7   | 800  | 0.3994          | 0.8650   |
+
+
+### Framework versions
+
+- Transformers 4.36.0
+- Pytorch 2.0.0
+- Datasets 2.1.0
+- Tokenizers 0.15.0

all_results.json

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+{
+    "epoch": 2.99,
+    "eval_accuracy": 0.867502898703489,
+    "eval_loss": 0.3935542702674866,
+    "eval_runtime": 398.9975,
+    "eval_samples_per_second": 95.108,
+    "eval_steps_per_second": 1.486
+}

eval_results.json

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+{
+    "epoch": 2.99,
+    "eval_accuracy": 0.867502898703489,
+    "eval_loss": 0.3935542702674866,
+    "eval_runtime": 398.9975,
+    "eval_samples_per_second": 95.108,
+    "eval_steps_per_second": 1.486
+}