---
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-2.0-armenian-colab-CV17.0_10epochs
  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: 0.12119113573407202
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# w2v-bert-2.0-armenian-colab-CV17.0_10epochs

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: 0.1461
- Wer: 0.1212
- Cer: 0.0217

## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 1.9136        | 1.0   | 325  | 0.2261          | 0.2817 | 0.0493 |
| 0.1872        | 2.0   | 650  | 0.1762          | 0.2208 | 0.0385 |
| 0.1168        | 3.0   | 975  | 0.1590          | 0.1807 | 0.0323 |
| 0.0817        | 4.0   | 1300 | 0.1444          | 0.1614 | 0.0287 |
| 0.058         | 5.0   | 1625 | 0.1414          | 0.1463 | 0.0259 |
| 0.0426        | 6.0   | 1950 | 0.1431          | 0.1447 | 0.0257 |
| 0.0284        | 7.0   | 2275 | 0.1333          | 0.1390 | 0.0251 |
| 0.0185        | 8.0   | 2600 | 0.1353          | 0.1254 | 0.0225 |
| 0.0114        | 9.0   | 2925 | 0.1434          | 0.1233 | 0.0219 |
| 0.007         | 10.0  | 3250 | 0.1461          | 0.1212 | 0.0217 |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1