---
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: 0.9963132675846669
    - name: Bleu
      type: bleu
      value: 0.0
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# 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: 2.4706
- Wer: 0.9963
- Cer: 0.6333
- Bleu: 0.0

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:----:|
| 8.3205        | 6.25  | 100  | 3.8395          | 1.0415 | 0.8830 | 0.0  |
| 3.3463        | 12.5  | 200  | 3.2263          | 1.0230 | 0.8113 | 0.0  |
| 3.0206        | 18.75 | 300  | 3.0363          | 1.0047 | 0.8167 | 0.0  |
| 2.7973        | 25.0  | 400  | 2.8782          | 1.0023 | 0.7764 | 0.0  |
| 2.4269        | 31.25 | 500  | 2.6308          | 1.0027 | 0.6957 | 0.0  |
| 2.0251        | 37.5  | 600  | 2.4706          | 0.9963 | 0.6333 | 0.0  |


### Framework versions

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