---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: hiera-finetuned-stroke-multi-ultrasound-combined
  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. -->

# hiera-finetuned-stroke-multi-ultrasound-combined

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3436
- Accuracy: 0.8661
- F1: 0.8650
- Precision: 0.8650
- Recall: 0.8661

## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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_with_restarts
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 12
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.5712        | 1.7964  | 100  | 0.4956          | 0.7923   | 0.7933 | 0.7973    | 0.7923 |
| 0.4495        | 3.5792  | 200  | 0.4193          | 0.8309   | 0.8315 | 0.8325    | 0.8309 |
| 0.4266        | 5.3620  | 300  | 0.4364          | 0.8150   | 0.8091 | 0.8221    | 0.8150 |
| 0.3375        | 7.1448  | 400  | 0.3775          | 0.8513   | 0.8473 | 0.8535    | 0.8513 |
| 0.2979        | 8.9412  | 500  | 0.3360          | 0.8627   | 0.8617 | 0.8614    | 0.8627 |
| 0.2703        | 10.7240 | 600  | 0.3436          | 0.8661   | 0.8650 | 0.8650    | 0.8661 |


### Framework versions

- Transformers 4.53.1
- Pytorch 2.7.1+cu126
- Datasets 3.6.0
- Tokenizers 0.21.2