---
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: testing_tensorboard_w_new_access_token
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_17_0
      type: common_voice_17_0
      config: hy-AM
      split: test
      args: hy-AM
    metrics:
    - name: Wer
      type: wer
      value: 1.0
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# testing_tensorboard_w_new_access_token

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: 3.1867
- Wer: 1.0
- Cer: 0.9653

## 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: 0.0001
- 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: constant
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|
| 3.3114        | 0.6154 | 200  | 3.2030          | 1.0    | 1.0    |
| 3.1797        | 1.2308 | 400  | 3.1973          | 1.0    | 1.0    |
| 3.1791        | 1.8462 | 600  | 3.1899          | 1.0    | 1.0    |
| 3.1767        | 2.4615 | 800  | 3.1787          | 1.0    | 1.0    |
| 3.1681        | 3.0769 | 1000 | 3.1870          | 1.0    | 0.9987 |
| 3.1783        | 3.6923 | 1200 | 3.1996          | 0.9998 | 0.9822 |
| 3.167         | 4.3077 | 1400 | 3.1726          | 1.0    | 1.0    |
| 3.171         | 4.9231 | 1600 | 3.1743          | 1.0    | 0.9653 |
| 3.1654        | 5.5385 | 1800 | 3.1926          | 1.0000 | 0.9487 |
| 3.1714        | 6.1538 | 2000 | 3.1700          | 1.0    | 0.9653 |
| 3.1638        | 6.7692 | 2200 | 3.1688          | 1.0    | 0.9653 |
| 3.164         | 7.3846 | 2400 | 3.1934          | 1.0000 | 0.9487 |
| 3.1729        | 8.0    | 2600 | 3.1689          | 1.0    | 0.9653 |
| 3.1652        | 8.6154 | 2800 | 3.1660          | 1.0    | 0.9653 |
| 3.1569        | 9.2308 | 3000 | 3.1890          | 1.0000 | 0.9487 |
| 3.1639        | 9.8462 | 3200 | 3.1867          | 1.0    | 0.9653 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1