---
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: 0.41655589677774213
      name: Wer
    - type: bleu
      value: 0.3602695476100989
      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: 0.3166
- Wer: 0.4166
- Cer: 0.0689
- Bleu: 0.3603

## 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   |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:------:|
| 11.8671       | 3.125  | 50   | 3.8104          | 1.0011 | 0.9249 | 0.0    |
| 1.5965        | 6.25   | 100  | 0.2796          | 0.4122 | 0.0680 | 0.3517 |
| 0.2054        | 9.375  | 150  | 0.2320          | 0.3751 | 0.0620 | 0.4040 |
| 0.1702        | 12.5   | 200  | 0.2367          | 0.3794 | 0.0633 | 0.3939 |
| 0.1495        | 15.625 | 250  | 0.2527          | 0.4168 | 0.0680 | 0.3457 |
| 0.1457        | 18.75  | 300  | 0.2536          | 0.3973 | 0.0662 | 0.3723 |
| 0.1264        | 21.875 | 350  | 0.2765          | 0.4175 | 0.0693 | 0.3546 |
| 0.1092        | 25.0   | 400  | 0.2711          | 0.4032 | 0.0673 | 0.3701 |
| 0.0952        | 28.125 | 450  | 0.2828          | 0.4139 | 0.0691 | 0.3605 |
| 0.0919        | 31.25  | 500  | 0.2972          | 0.4283 | 0.0721 | 0.3355 |
| 0.0909        | 34.375 | 550  | 0.2971          | 0.4155 | 0.0686 | 0.3567 |
| 0.0744        | 37.5   | 600  | 0.3086          | 0.4241 | 0.0705 | 0.3461 |
| 0.069         | 40.625 | 650  | 0.3166          | 0.4166 | 0.0689 | 0.3603 |


### Framework versions

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