---
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: wav2vec2-large-xls-r-300m-test1yakutsi-colab
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_17_0
      type: common_voice_17_0
      config: sah
      split: test
      args: sah
    metrics:
    - name: Wer
      type: wer
      value: 0.4245327102803738
pipeline_tag: automatic-speech-recognition
---

<!-- 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. -->

# wav2vec2-large-xls-r-300m-test1yakutsi-colab

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: 0.4509
- Wer: 0.4245

## 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: 0.0002
- 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: 250
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 3.1089        | 1.1707 | 120  | 2.9271          | 1.0    |
| 2.1217        | 2.3415 | 240  | 0.8076          | 0.7261 |
| 0.5442        | 3.5122 | 360  | 0.4935          | 0.5490 |
| 0.3041        | 4.6829 | 480  | 0.4464          | 0.4832 |
| 0.2184        | 5.8537 | 600  | 0.4263          | 0.4554 |
| 0.1675        | 7.0244 | 720  | 0.4416          | 0.4488 |
| 0.138         | 8.1951 | 840  | 0.4512          | 0.4380 |
| 0.1167        | 9.3659 | 960  | 0.4509          | 0.4245 |


### Framework versions

- Transformers 4.41.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1