---
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       |


### Framework versions

- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1