---
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: 0.5038262932638631
    - name: Bleu
      type: bleu
      value: 0.25352723931305554
---

<!-- 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: 0.5467
- Wer: 0.5038
- Cer: 0.0871
- Bleu: 0.2535

## 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   |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|
| 7.5761        | 100.0 | 100  | 0.3128          | 0.4455 | 0.0729 | 0.3095 |
| 0.067         | 200.0 | 200  | 0.3441          | 0.4234 | 0.0706 | 0.3389 |
| 0.0307        | 300.0 | 300  | 0.3906          | 0.4489 | 0.0749 | 0.3100 |
| 0.0251        | 400.0 | 400  | 0.4461          | 0.4745 | 0.0802 | 0.2744 |
| 0.0205        | 500.0 | 500  | 0.4579          | 0.4834 | 0.0820 | 0.2714 |
| 0.0166        | 600.0 | 600  | 0.4550          | 0.4742 | 0.0823 | 0.2837 |
| 0.0123        | 700.0 | 700  | 0.5467          | 0.5038 | 0.0871 | 0.2535 |


### Framework versions

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