---
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: results
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_17_0
      type: common_voice_17_0
      config: ne-NP
      split: validated+other
      args: ne-NP
    metrics:
    - name: Wer
      type: wer
      value: 0.5865921787709497
---

<!-- 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. -->

# results

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: 0.7289
- Wer: 0.5866

## 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: 200
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 1.4919        | 2.9851  | 100  | 1.2236          | 0.9106 |
| 1.0086        | 5.9701  | 200  | 0.9436          | 0.8291 |
| 0.6072        | 8.9552  | 300  | 0.8277          | 0.7117 |
| 0.55          | 11.9403 | 400  | 0.7774          | 0.6726 |
| 0.3398        | 14.9254 | 500  | 0.7344          | 0.6212 |
| 0.2543        | 17.9104 | 600  | 0.7368          | 0.6212 |
| 0.3558        | 20.8955 | 700  | 0.7313          | 0.5788 |
| 0.1751        | 23.8806 | 800  | 0.7060          | 0.5855 |
| 0.1502        | 26.8657 | 900  | 0.7289          | 0.5866 |


### Framework versions

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