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---
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
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