---
library_name: transformers
license: cc-by-nc-4.0
base_model: facebook/mms-1b-all
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
- bleu
model-index:
- name: wav2vec2-mms-1b-CV17.0-training_set_variations
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_17_0
      type: common_voice_17_0
      config: ta
      split: validation
      args: ta
    metrics:
    - name: Wer
      type: wer
      value: 0.38488334784800843
    - name: Bleu
      type: bleu
      value: 0.3848277074951031
---

<!-- 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-mms-1b-CV17.0-training_set_variations

This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2335
- Wer: 0.3849
- Cer: 0.0627
- Bleu: 0.3848

## 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_ratio: 0.15
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    | Cer    | Bleu   |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|:------:|
| 12.5537       | 1.5625  | 50   | 3.9513          | 1.0006 | 0.9854 | 0.0    |
| 2.2034        | 3.125   | 100  | 0.3019          | 0.4137 | 0.0683 | 0.3510 |
| 0.226         | 4.6875  | 150  | 0.2305          | 0.3794 | 0.0623 | 0.3981 |
| 0.1904        | 6.25    | 200  | 0.2262          | 0.3776 | 0.0618 | 0.3988 |
| 0.1798        | 7.8125  | 250  | 0.2275          | 0.3760 | 0.0621 | 0.4040 |
| 0.1724        | 9.375   | 300  | 0.2399          | 0.4021 | 0.0659 | 0.3610 |
| 0.1791        | 10.9375 | 350  | 0.2310          | 0.3883 | 0.0635 | 0.3797 |
| 0.1678        | 12.5    | 400  | 0.2405          | 0.3961 | 0.0666 | 0.3722 |
| 0.1527        | 14.0625 | 450  | 0.2335          | 0.3849 | 0.0627 | 0.3848 |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1