---
library_name: transformers
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: w2v-bert-cv-grain-lg_cv_only
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_17_0
      type: common_voice_17_0
      config: lg
      split: test[:10%]
      args: lg
    metrics:
    - name: Wer
      type: wer
      value: 0.5799642969652421
---

<!-- 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. -->

# w2v-bert-cv-grain-lg_cv_only

This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: inf
- Wer: 0.5800
- Cer: 0.1379

## 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: 5e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
| 0.5013        | 1.0   | 2221  | inf             | 0.2789 | 0.0724 |
| 0.299         | 2.0   | 4442  | inf             | 0.2501 | 0.0648 |
| 0.2554        | 3.0   | 6663  | inf             | 0.2435 | 0.0685 |
| 0.2411        | 4.0   | 8884  | inf             | 0.2447 | 0.0648 |
| 0.2886        | 5.0   | 11105 | inf             | 0.2506 | 0.0654 |
| 0.3923        | 6.0   | 13326 | inf             | 0.4237 | 0.1108 |
| 2.1779        | 7.0   | 15547 | inf             | 0.5612 | 0.1439 |
| 4.5629        | 8.0   | 17768 | inf             | 0.5152 | 0.1379 |
| 2.236         | 9.0   | 19989 | inf             | 0.5787 | 0.1384 |
| 2.2033        | 10.0  | 22210 | inf             | 0.5742 | 0.1375 |
| 2.2047        | 11.0  | 24431 | inf             | 0.5784 | 0.1382 |
| 2.2057        | 12.0  | 26652 | inf             | 0.5805 | 0.1390 |
| 2.2076        | 13.0  | 28873 | inf             | 0.5800 | 0.1379 |


### Framework versions

- Transformers 4.46.1
- Pytorch 2.1.0+cu118
- Datasets 3.1.0
- Tokenizers 0.20.1