---
library_name: transformers
license: apache-2.0
base_model: SZTAKI-HLT/hubert-base-cc
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: husst-hubert-hungarian
  results: []
datasets:
- ariel-ml/HuSST-augmented
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# husst-hubert-hungarian

This model is a fine-tuned version of [SZTAKI-HLT/hubert-base-cc](https://huggingface.co/SZTAKI-HLT/hubert-base-cc) on [ariel-ml/HuSST-augmented](https://huggingface.co/datasets/ariel-ml/HuSST-augmented) dataset.

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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: 4

### Results
It achieves the following results on the evaluation set:
```text
              precision    recall  f1-score   support

           0       0.77      0.90      0.83       697
           1       0.79      0.54      0.64       435
           2       0.45      0.67      0.54        33

    accuracy                           0.76      1165
   macro avg       0.67      0.70      0.67      1165
weighted avg       0.77      0.76      0.75      1165
```

### Framework versions

- Transformers 4.48.0
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0