pytorch tensorboard 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-colab
  results: []
---

<!-- 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-turkish-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 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7532
- Wer: 0.4020

## 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 5.9542        | 1.96  | 400  | 1.5737          | 0.8827 |
| 0.8596        | 3.92  | 800  | 0.7296          | 0.5696 |
| 0.4729        | 5.88  | 1200 | 0.6004          | 0.4934 |
| 0.3364        | 7.84  | 1600 | 0.5776          | 0.4656 |
| 0.2684        | 9.8   | 2000 | 0.6178          | 0.4563 |
| 0.2143        | 11.76 | 2400 | 0.6408          | 0.4690 |
| 0.1744        | 13.72 | 2800 | 0.6704          | 0.4573 |
| 0.1458        | 15.68 | 3200 | 0.7015          | 0.4484 |
| 0.1201        | 17.65 | 3600 | 0.7151          | 0.4228 |
| 0.104         | 19.61 | 4000 | 0.7123          | 0.4195 |
| 0.0887        | 21.57 | 4400 | 0.7102          | 0.4234 |
| 0.0807        | 23.53 | 4800 | 0.7561          | 0.4132 |
| 0.0697        | 25.49 | 5200 | 0.7435          | 0.4075 |
| 0.0611        | 27.45 | 5600 | 0.7465          | 0.4034 |
| 0.0556        | 29.41 | 6000 | 0.7532          | 0.4020 |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1
