---
license: apache-2.0
tags:
- generated_from_trainer
base_model: facebook/wav2vec2-xls-r-300m
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: xls-r-300-cv17-bulgarian-adap-ru
  results:
  - task:
      type: automatic-speech-recognition
      name: Automatic Speech Recognition
    dataset:
      name: common_voice_17_0
      type: common_voice_17_0
      config: bg
      split: validation
      args: bg
    metrics:
    - type: wer
      value: 0.3184421100534719
      name: Wer
---

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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/badr-nlp/xlsr-continual-finetuning-polish/runs/2220fmjr)
# xls-r-300-cv17-bulgarian-adap-ru

This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3848
- Wer: 0.3184
- Cer: 0.0766

## 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: 0.0003
- 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: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
| 3.1611        | 0.6579  | 100  | 3.1566          | 1.0    | 1.0    |
| 1.4834        | 1.3158  | 200  | 1.5156          | 0.9683 | 0.3419 |
| 0.5874        | 1.9737  | 300  | 0.5361          | 0.6018 | 0.1459 |
| 0.312         | 2.6316  | 400  | 0.3991          | 0.4526 | 0.1071 |
| 0.2139        | 3.2895  | 500  | 0.3913          | 0.4365 | 0.1053 |
| 0.2653        | 3.9474  | 600  | 0.3756          | 0.4114 | 0.0997 |
| 0.186         | 4.6053  | 700  | 0.3684          | 0.4057 | 0.0971 |
| 0.1569        | 5.2632  | 800  | 0.3831          | 0.4182 | 0.0996 |
| 0.1635        | 5.9211  | 900  | 0.3577          | 0.3803 | 0.0914 |
| 0.0962        | 6.5789  | 1000 | 0.3461          | 0.3620 | 0.0868 |
| 0.2232        | 7.2368  | 1100 | 0.3705          | 0.3596 | 0.0856 |
| 0.1456        | 7.8947  | 1200 | 0.3722          | 0.3643 | 0.0880 |
| 0.0846        | 8.5526  | 1300 | 0.3657          | 0.3565 | 0.0839 |
| 0.0874        | 9.2105  | 1400 | 0.3836          | 0.3418 | 0.0814 |
| 0.1059        | 9.8684  | 1500 | 0.3634          | 0.3397 | 0.0808 |
| 0.0719        | 10.5263 | 1600 | 0.3741          | 0.3468 | 0.0838 |
| 0.0681        | 11.1842 | 1700 | 0.3757          | 0.3396 | 0.0817 |
| 0.0701        | 11.8421 | 1800 | 0.3892          | 0.3324 | 0.0804 |
| 0.043         | 12.5    | 1900 | 0.3892          | 0.3315 | 0.0797 |
| 0.0482        | 13.1579 | 2000 | 0.3905          | 0.3213 | 0.0768 |
| 0.0279        | 13.8158 | 2100 | 0.3826          | 0.3185 | 0.0761 |
| 0.0609        | 14.4737 | 2200 | 0.3848          | 0.3184 | 0.0766 |


### Framework versions

- Transformers 4.42.0.dev0
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1