---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_8_0
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-tr-colab
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_8_0
      type: common_voice_8_0
      config: sw
      split: test[:400]
      args: sw
    metrics:
    - name: Wer
      type: wer
      value: 0.97
---

<!-- 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-tr-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_8_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4900
- Wer: 0.97

## 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: 50
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 6.5497        | 0.4   | 50   | 2.9819          | 1.0    |
| 2.8809        | 0.8   | 100  | 2.8873          | 1.0    |
| 2.8416        | 1.2   | 150  | 2.8427          | 1.0    |
| 2.8145        | 1.6   | 200  | 2.8067          | 1.0    |
| 2.747         | 2.0   | 250  | 2.7092          | 1.0    |
| 2.1095        | 2.4   | 300  | 1.3472          | 1.0    |
| 0.9546        | 2.8   | 350  | 0.7708          | 0.9975 |
| 0.6104        | 3.2   | 400  | 0.6317          | 0.9825 |
| 0.4941        | 3.6   | 450  | 0.5427          | 0.97   |
| 0.4345        | 4.0   | 500  | 0.5314          | 0.975  |
| 0.3327        | 4.4   | 550  | 0.4927          | 0.9625 |
| 0.3099        | 4.8   | 600  | 0.4900          | 0.97   |


### Framework versions

- Transformers 4.27.4
- Pytorch 1.13.1+cu116
- Datasets 2.11.0
- Tokenizers 0.13.2