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---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: hiera-finetuned-busi
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-busi
This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1380
- Accuracy: 0.9679
- F1: 0.9678
- Precision: 0.9678
- Recall: 0.9679
## 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: 48
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.2276 | 10.0 | 100 | 0.1666 | 0.9615 | 0.9611 | 0.9640 | 0.9615 |
| 0.1447 | 20.0 | 200 | 0.1826 | 0.9359 | 0.9352 | 0.9426 | 0.9359 |
| 0.0882 | 30.0 | 300 | 0.1612 | 0.9615 | 0.9612 | 0.9613 | 0.9615 |
| 0.0606 | 40.0 | 400 | 0.1380 | 0.9679 | 0.9678 | 0.9678 | 0.9679 |
### Framework versions
- Transformers 4.53.1
- Pytorch 2.7.1+cu126
- Datasets 3.6.0
- Tokenizers 0.21.2
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