---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- common_voice_16_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-hi-colab
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_16_0
      type: common_voice_16_0
      config: hi
      split: test
      args: hi
    metrics:
    - name: Wer
      type: wer
      value: 0.4948465637275874
---

<!-- 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-hi-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_16_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6983
- Wer: 0.4948

## 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: 30

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 5.491         | 1.8059  | 400  | 1.3703          | 0.9679 |
| 0.6981        | 3.6117  | 800  | 0.7041          | 0.6607 |
| 0.3758        | 5.4176  | 1200 | 0.6709          | 0.6185 |
| 0.2736        | 7.2235  | 1600 | 0.7170          | 0.5925 |
| 0.2089        | 9.0293  | 2000 | 0.6445          | 0.5722 |
| 0.1686        | 10.8352 | 2400 | 0.7004          | 0.5770 |
| 0.1408        | 12.6411 | 2800 | 0.7097          | 0.5735 |
| 0.1227        | 14.4470 | 3200 | 0.6763          | 0.5533 |
| 0.1056        | 16.2528 | 3600 | 0.7245          | 0.5484 |
| 0.0923        | 18.0587 | 4000 | 0.7198          | 0.5480 |
| 0.083         | 19.8646 | 4400 | 0.6568          | 0.5251 |
| 0.0742        | 21.6704 | 4800 | 0.7183          | 0.5252 |
| 0.0647        | 23.4763 | 5200 | 0.7306          | 0.5141 |
| 0.0574        | 25.2822 | 5600 | 0.7236          | 0.5063 |
| 0.052         | 27.0880 | 6000 | 0.7234          | 0.4969 |
| 0.0478        | 28.8939 | 6400 | 0.6983          | 0.4948 |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1