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---
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-large-mms-1b-uyghur-latin
  results: []
language:
- ug
---

<!-- 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. -->

# wav2vec2-large-mms-1b-uyghur-latin

This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the None dataset.
It achieves the following best results on the evaluation set:

- Best Wer: 30.8949%
- Best Cer: 5.9823 %

## Training procedure

Finetuning code avaiblable in https://github.com/ixxan/ug-speech

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer Ortho | Cer Ortho |
|:-------------:|:------:|:----:|:---------------:|:---------:|:---------:|
| 0.3425        | 1.0006 | 1313 | 0.3081          | 35.3122   | 6.8424    |
| 0.3218        | 2.0011 | 2626 | 0.2771          | 31.7204   | 6.1840    |
| 0.3012        | 3.0017 | 3939 | 0.2739          | 30.8949   | 5.9823    |
| 0.2961        | 3.9989 | 5248 | 0.2771          | 31.7116   | 6.1806    |

### Framework versions

- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3