---
base_model: facebook/mms-1b-all
datasets:
- common_voice_17_0
library_name: transformers
license: cc-by-nc-4.0
metrics:
- wer
- bleu
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-mms-1b-CV17.0-training_set_variations
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: common_voice_17_0
      type: common_voice_17_0
      config: ta
      split: validation
      args: ta
    metrics:
    - type: wer
      value: 0.4250355227574827
      name: Wer
    - type: bleu
      value: 0.3461897882903843
      name: Bleu
---

<!-- 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: 0.3320
- Wer: 0.4250
- Cer: 0.0720
- Bleu: 0.3462

## 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   |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
| 11.5156       | 6.25  | 50   | 5.5076          | 1.0    | 0.9701 | 0.0    |
| 1.8133        | 12.5  | 100  | 0.2759          | 0.4067 | 0.0674 | 0.3610 |
| 0.1751        | 18.75 | 150  | 0.2414          | 0.3828 | 0.0639 | 0.3924 |
| 0.1315        | 25.0  | 200  | 0.2556          | 0.3887 | 0.0649 | 0.3901 |
| 0.1           | 31.25 | 250  | 0.2842          | 0.4168 | 0.0700 | 0.3520 |
| 0.0842        | 37.5  | 300  | 0.2997          | 0.4133 | 0.0699 | 0.3571 |
| 0.0717        | 43.75 | 350  | 0.3210          | 0.4260 | 0.0732 | 0.3431 |
| 0.0608        | 50.0  | 400  | 0.3320          | 0.4250 | 0.0720 | 0.3462 |


### Framework versions

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