---
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: 0.45588302699729566
      name: Wer
    - type: bleu
      value: 0.30120570288375
      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: 0.4242
- Wer: 0.4559
- Cer: 0.0764
- Bleu: 0.3012

## 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   |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
| 13.1596       | 12.5  | 50   | 6.8694          | 1.0    | 0.9625 | 0.0    |
| 3.2131        | 25.0  | 100  | 0.4085          | 0.4707 | 0.0784 | 0.2830 |
| 0.1719        | 37.5  | 150  | 0.2583          | 0.3920 | 0.0650 | 0.3818 |
| 0.0962        | 50.0  | 200  | 0.2869          | 0.4118 | 0.0682 | 0.3547 |
| 0.0648        | 62.5  | 250  | 0.3209          | 0.4213 | 0.0696 | 0.3435 |
| 0.0613        | 75.0  | 300  | 0.3404          | 0.4454 | 0.0742 | 0.3200 |
| 0.0515        | 87.5  | 350  | 0.3744          | 0.4385 | 0.0734 | 0.3289 |
| 0.0426        | 100.0 | 400  | 0.3835          | 0.4479 | 0.0748 | 0.3078 |
| 0.0384        | 112.5 | 450  | 0.3776          | 0.4432 | 0.0746 | 0.3243 |
| 0.0363        | 125.0 | 500  | 0.4053          | 0.4371 | 0.0732 | 0.3251 |
| 0.0385        | 137.5 | 550  | 0.4225          | 0.4520 | 0.0772 | 0.3115 |
| 0.0343        | 150.0 | 600  | 0.4295          | 0.4463 | 0.0758 | 0.3167 |
| 0.0371        | 162.5 | 650  | 0.4242          | 0.4559 | 0.0764 | 0.3012 |


### Framework versions

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