---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: xlsr-sl-adap-ru
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_17_0
      type: common_voice_17_0
      config: sl
      split: validation
      args: sl
    metrics:
    - name: Wer
      type: wer
      value: 0.45177304964539006
---

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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-hebrew/runs/ulg42ec9)
# xlsr-sl-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: 0.4726
- Wer: 0.4518
- Cer: 0.1009

## 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: 3e-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: 50
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    | Cer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|:------:|
| 12.5552       | 2.2989  | 100  | 13.9758         | 1.0189 | 0.8746 |
| 3.2145        | 4.5977  | 200  | 3.1893          | 1.0    | 1.0    |
| 3.0478        | 6.8966  | 300  | 3.0401          | 1.0    | 1.0    |
| 2.8114        | 9.1954  | 400  | 2.7815          | 1.0    | 1.0    |
| 1.6159        | 11.4943 | 500  | 1.1846          | 0.8243 | 0.2357 |
| 0.7215        | 13.7931 | 600  | 0.6544          | 0.6268 | 0.1437 |
| 0.4679        | 16.0920 | 700  | 0.5544          | 0.5789 | 0.1304 |
| 0.5392        | 18.3908 | 800  | 0.5222          | 0.5383 | 0.1212 |
| 0.3497        | 20.6897 | 900  | 0.4828          | 0.5157 | 0.1153 |
| 0.3216        | 22.9885 | 1000 | 0.4861          | 0.5118 | 0.1128 |
| 0.3924        | 25.2874 | 1100 | 0.4713          | 0.4879 | 0.1088 |
| 0.3363        | 27.5862 | 1200 | 0.4800          | 0.4759 | 0.1059 |
| 0.3672        | 29.8851 | 1300 | 0.4664          | 0.4725 | 0.1046 |
| 0.2735        | 32.1839 | 1400 | 0.4708          | 0.4725 | 0.1046 |
| 0.2           | 34.4828 | 1500 | 0.4790          | 0.4652 | 0.1040 |
| 0.3515        | 36.7816 | 1600 | 0.4688          | 0.4577 | 0.1018 |
| 0.3233        | 39.0805 | 1700 | 0.4734          | 0.4593 | 0.1019 |
| 0.2715        | 41.3793 | 1800 | 0.4670          | 0.4516 | 0.1003 |
| 0.2793        | 43.6782 | 1900 | 0.4727          | 0.4556 | 0.1014 |
| 0.2367        | 45.9770 | 2000 | 0.4729          | 0.4552 | 0.1008 |
| 0.2503        | 48.2759 | 2100 | 0.4726          | 0.4518 | 0.1009 |


### Framework versions

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