pytorch wav2vec2 automatic-speech-recognition dataset:common_voice transformers generated_from_trainer license:apache-2.0 model-index
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: wav2vec2-large-xls-r-300m-turkish-colab2
  results: []
---

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# wav2vec2-large-xls-r-300m-turkish-colab2

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 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3738
- Wer: 0.3532

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.9022        | 3.7   | 400  | 0.6778          | 0.7414 |
| 0.4106        | 7.4   | 800  | 0.4123          | 0.5049 |
| 0.1862        | 11.11 | 1200 | 0.4260          | 0.4232 |
| 0.1342        | 14.81 | 1600 | 0.3951          | 0.4097 |
| 0.0997        | 18.51 | 2000 | 0.4100          | 0.3999 |
| 0.0782        | 22.22 | 2400 | 0.3918          | 0.3875 |
| 0.059         | 25.92 | 2800 | 0.3803          | 0.3698 |
| 0.0474        | 29.63 | 3200 | 0.3738          | 0.3532 |


### Framework versions

- Transformers 4.19.2
- Pytorch 1.11.0+cu113
- Datasets 2.2.2
- Tokenizers 0.12.1
