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---
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-147-upper-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
---

<!-- 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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/badr-nlp/xlsr-continual-finetuning-new/runs/mfm1kgzn)
# mHuBERT-147-upper-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: 3.2172
- 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: 0.001
- 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

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer | Cer |
|:-------------:|:-------:|:----:|:---------------:|:---:|:---:|
| 3.8611        | 3.9216  | 100  | 3.8610          | 1.0 | 1.0 |
| 3.2233        | 7.8431  | 200  | 3.2270          | 1.0 | 1.0 |
| 3.1742        | 11.7647 | 300  | 3.2232          | 1.0 | 1.0 |
| 3.2292        | 15.6863 | 400  | 3.2238          | 1.0 | 1.0 |
| 3.2105        | 19.6078 | 500  | 3.2270          | 1.0 | 1.0 |
| 3.191         | 23.5294 | 600  | 3.2201          | 1.0 | 1.0 |
| 3.2626        | 27.4510 | 700  | 3.2177          | 1.0 | 1.0 |
| 3.21          | 31.3725 | 800  | 3.2230          | 1.0 | 1.0 |
| 3.1871        | 35.2941 | 900  | 3.2211          | 1.0 | 1.0 |
| 3.2221        | 39.2157 | 1000 | 3.2245          | 1.0 | 1.0 |
| 3.2408        | 43.1373 | 1100 | 3.2217          | 1.0 | 1.0 |
| 3.2           | 47.0588 | 1200 | 3.2193          | 1.0 | 1.0 |
| 3.202         | 50.9804 | 1300 | 3.2181          | 1.0 | 1.0 |
| 3.2286        | 54.9020 | 1400 | 3.2190          | 1.0 | 1.0 |
| 3.1863        | 58.8235 | 1500 | 3.2187          | 1.0 | 1.0 |
| 3.1868        | 62.7451 | 1600 | 3.2175          | 1.0 | 1.0 |
| 3.226         | 66.6667 | 1700 | 3.2199          | 1.0 | 1.0 |
| 3.1944        | 70.5882 | 1800 | 3.2196          | 1.0 | 1.0 |
| 3.1997        | 74.5098 | 1900 | 3.2180          | 1.0 | 1.0 |
| 3.2184        | 78.4314 | 2000 | 3.2200          | 1.0 | 1.0 |
| 3.2252        | 82.3529 | 2100 | 3.2188          | 1.0 | 1.0 |
| 3.208         | 86.2745 | 2200 | 3.2175          | 1.0 | 1.0 |
| 3.2122        | 90.1961 | 2300 | 3.2170          | 1.0 | 1.0 |
| 3.2307        | 94.1176 | 2400 | 3.2169          | 1.0 | 1.0 |
| 3.1852        | 98.0392 | 2500 | 3.2172          | 1.0 | 1.0 |


### Framework versions

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