| --- |
| library_name: transformers |
| license: apache-2.0 |
| base_model: facebook/deit-tiny-distilled-patch16-224 |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: deit-tiny-distilled-patch16-224emotion_model_binary_deit |
| 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. --> |
|
|
| # deit-tiny-distilled-patch16-224emotion_model_binary_deit |
| |
| This model is a fine-tuned version of [facebook/deit-tiny-distilled-patch16-224](https://huggingface.co/facebook/deit-tiny-distilled-patch16-224) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.7254 |
| - Accuracy: 0.9056 |
| - Weighted f1: 0.9056 |
| - Micro f1: 0.9056 |
| - Macro f1: 0.9056 |
| - Weighted recall: 0.9056 |
| - Micro recall: 0.9056 |
| - Macro recall: 0.9056 |
| |
| ## 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: 5e-05 |
| - train_batch_size: 64 |
| - eval_batch_size: 8 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - num_epochs: 10 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted f1 | Micro f1 | Macro f1 | Weighted recall | Micro recall | Macro recall | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:| |
| | 0.4537 | 1.0 | 401 | 0.3859 | 0.8234 | 0.8219 | 0.8234 | 0.8219 | 0.8234 | 0.8234 | 0.8234 | |
| | 0.3044 | 2.0 | 802 | 0.3653 | 0.8422 | 0.8411 | 0.8422 | 0.8411 | 0.8422 | 0.8422 | 0.8422 | |
| | 0.1886 | 3.0 | 1203 | 0.2977 | 0.8859 | 0.8859 | 0.8859 | 0.8859 | 0.8859 | 0.8859 | 0.8859 | |
| | 0.093 | 4.0 | 1604 | 0.3351 | 0.8972 | 0.8972 | 0.8972 | 0.8972 | 0.8972 | 0.8972 | 0.8972 | |
| | 0.048 | 5.0 | 2005 | 0.4311 | 0.9025 | 0.9025 | 0.9025 | 0.9025 | 0.9025 | 0.9025 | 0.9025 | |
| | 0.0245 | 6.0 | 2406 | 0.5580 | 0.9034 | 0.9034 | 0.9034 | 0.9034 | 0.9034 | 0.9034 | 0.9034 | |
| | 0.0101 | 7.0 | 2807 | 0.6712 | 0.9044 | 0.9044 | 0.9044 | 0.9044 | 0.9044 | 0.9044 | 0.9044 | |
| | 0.0029 | 8.0 | 3208 | 0.7049 | 0.9041 | 0.9041 | 0.9041 | 0.9041 | 0.9041 | 0.9041 | 0.9041 | |
| | 0.0011 | 9.0 | 3609 | 0.7212 | 0.9047 | 0.9047 | 0.9047 | 0.9047 | 0.9047 | 0.9047 | 0.9047 | |
| | 0.0006 | 10.0 | 4010 | 0.7254 | 0.9056 | 0.9056 | 0.9056 | 0.9056 | 0.9056 | 0.9056 | 0.9056 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.57.1 |
| - Pytorch 2.8.0+cu126 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.1 |
|
|
