---
library_name: transformers
license: apache-2.0
base_model: timm/levit_128.fb_dist_in1k
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: levit_128.fb_dist_in1k-finetuned-stroke-binary
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# levit_128.fb_dist_in1k-finetuned-stroke-binary

This model is a fine-tuned version of [timm/levit_128.fb_dist_in1k](https://huggingface.co/timm/levit_128.fb_dist_in1k) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- Accuracy: 0.6974
- F1: 0.7014
- Precision: 0.7298
- Recall: 0.6974

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 36
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.695         | 0.6202 | 100  | nan             | 0.5364   | 0.5421 | 0.5541    | 0.5364 |
| 0.6804        | 1.2357 | 200  | nan             | 0.5798   | 0.5833 | 0.6278    | 0.5798 |
| 0.6821        | 1.8558 | 300  | nan             | 0.6232   | 0.6280 | 0.6413    | 0.6232 |
| 0.6726        | 2.4713 | 400  | nan             | 0.6671   | 0.6711 | 0.6829    | 0.6671 |
| 0.6546        | 3.0868 | 500  | nan             | 0.7024   | 0.7021 | 0.7018    | 0.7024 |
| 0.647         | 3.7070 | 600  | nan             | 0.7065   | 0.7093 | 0.7159    | 0.7065 |
| 0.6263        | 4.3225 | 700  | nan             | 0.6956   | 0.6991 | 0.7096    | 0.6956 |
| 0.6112        | 4.9426 | 800  | nan             | 0.6766   | 0.6807 | 0.7123    | 0.6766 |
| 0.5704        | 5.5581 | 900  | nan             | 0.6974   | 0.7014 | 0.7298    | 0.6974 |


### Framework versions

- Transformers 4.48.3
- Pytorch 2.6.0+cu124
- Datasets 3.4.0
- Tokenizers 0.21.0