pytorch tensorboard wav2vec2 automatic-speech-recognition tr-TR dataset:common_voice, common_voice_6_1_0 transformers generated_from_trainer hf-asr-leaderboard license:apache-2.0 model-index
---
license: apache-2.0
tags:
- generated_from_trainer
- hf-asr-leaderboard
datasets:
- common_voice, common_voice_6_1_0
model-index:
- name: wav2vec2-large-xls-r-300m-tr
  results: []
language:
- tr-TR
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# wav2vec2-large-xls-r-300m-tr

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: 0.2841
- Wer: 0.2904

## 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: 3e-05
- train_batch_size: 7
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 14
- 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 5.0805        | 4.03  | 1000 | 3.0333          | 1.0    |
| 1.5733        | 8.06  | 2000 | 0.5545          | 0.5080 |
| 0.6238        | 12.1  | 3000 | 0.3861          | 0.3977 |
| 0.4535        | 16.13 | 4000 | 0.3253          | 0.3408 |
| 0.3682        | 20.16 | 5000 | 0.3042          | 0.3177 |
| 0.3302        | 24.19 | 6000 | 0.2950          | 0.3015 |
| 0.2985        | 28.23 | 7000 | 0.2841          | 0.2904 |


### Framework versions

- Transformers 4.11.3
- Pytorch 1.10.0+cu113
- Datasets 1.18.3
- Tokenizers 0.10.3
