---
license: cc-by-nc-4.0
base_model: utter-project/mHuBERT-147
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: mHuBERT-147upper-sorbian
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_17_0
      type: common_voice_17_0
      config: hsb
      split: validation
      args: hsb
    metrics:
    - name: Wer
      type: wer
      value: 1.0
---

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# mHuBERT-147upper-sorbian

This model is a fine-tuned version of [utter-project/mHuBERT-147](https://huggingface.co/utter-project/mHuBERT-147) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 3.2170
- Wer: 1.0
- Cer: 1.0

## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer | Cer |
|:-------------:|:-------:|:----:|:---------------:|:---:|:---:|
| 7.2839        | 3.9216  | 100  | 7.4925          | 1.0 | 1.0 |
| 3.4632        | 7.8431  | 200  | 3.4671          | 1.0 | 1.0 |
| 3.181         | 11.7647 | 300  | 3.2306          | 1.0 | 1.0 |
| 3.2284        | 15.6863 | 400  | 3.2231          | 1.0 | 1.0 |
| 3.2113        | 19.6078 | 500  | 3.2243          | 1.0 | 1.0 |
| 3.1844        | 23.5294 | 600  | 3.2183          | 1.0 | 1.0 |
| 3.2644        | 27.4510 | 700  | 3.2180          | 1.0 | 1.0 |
| 3.2111        | 31.3725 | 800  | 3.2191          | 1.0 | 1.0 |
| 3.187         | 35.2941 | 900  | 3.2189          | 1.0 | 1.0 |
| 3.2133        | 39.2157 | 1000 | 3.2203          | 1.0 | 1.0 |
| 3.2406        | 43.1373 | 1100 | 3.2181          | 1.0 | 1.0 |
| 3.1993        | 47.0588 | 1200 | 3.2178          | 1.0 | 1.0 |
| 3.2036        | 50.9804 | 1300 | 3.2169          | 1.0 | 1.0 |
| 3.2283        | 54.9020 | 1400 | 3.2171          | 1.0 | 1.0 |
| 3.1854        | 58.8235 | 1500 | 3.2198          | 1.0 | 1.0 |
| 3.184         | 62.7451 | 1600 | 3.2182          | 1.0 | 1.0 |
| 3.2253        | 66.6667 | 1700 | 3.2194          | 1.0 | 1.0 |
| 3.1943        | 70.5882 | 1800 | 3.2194          | 1.0 | 1.0 |
| 3.201         | 74.5098 | 1900 | 3.2167          | 1.0 | 1.0 |
| 3.2178        | 78.4314 | 2000 | 3.2180          | 1.0 | 1.0 |
| 3.2252        | 82.3529 | 2100 | 3.2172          | 1.0 | 1.0 |
| 3.2081        | 86.2745 | 2200 | 3.2170          | 1.0 | 1.0 |
| 3.2125        | 90.1961 | 2300 | 3.2170          | 1.0 | 1.0 |
| 3.23          | 94.1176 | 2400 | 3.2170          | 1.0 | 1.0 |
| 3.1851        | 98.0392 | 2500 | 3.2170          | 1.0 | 1.0 |


### Framework versions

- Transformers 4.42.0.dev0
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1