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---
language:
- tr
license: apache-2.0
tags:
- automatic-speech-recognition
- common_voice
- generated_from_trainer
datasets:
- common_voice
metrics:
- wer
model-index:
- name: wav2vec2-common_voice-tr-demo
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: COMMON_VOICE - TR
type: common_voice
config: tr
split: test
args: 'Config: tr, Training split: train+validation, Eval split: test'
metrics:
- name: Wer
type: wer
value: 0.3446021856807272
---
<!-- 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-common_voice-tr-demo
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the COMMON_VOICE - TR dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3794
- Wer: 0.3446
## 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: 15.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log | 0.92 | 100 | 3.5956 | 1.0 |
| No log | 1.83 | 200 | 3.0269 | 0.9999 |
| No log | 2.75 | 300 | 0.9827 | 0.8111 |
| No log | 3.67 | 400 | 0.6236 | 0.6304 |
| 3.1866 | 4.59 | 500 | 0.5016 | 0.5264 |
| 3.1866 | 5.5 | 600 | 0.4523 | 0.4935 |
| 3.1866 | 6.42 | 700 | 0.4306 | 0.4528 |
| 3.1866 | 7.34 | 800 | 0.4328 | 0.4329 |
| 3.1866 | 8.26 | 900 | 0.4026 | 0.4105 |
| 0.227 | 9.17 | 1000 | 0.4096 | 0.4080 |
| 0.227 | 10.09 | 1100 | 0.3921 | 0.3915 |
| 0.227 | 11.01 | 1200 | 0.3830 | 0.3778 |
| 0.227 | 11.93 | 1300 | 0.3846 | 0.3616 |
| 0.227 | 12.84 | 1400 | 0.3888 | 0.3619 |
| 0.1046 | 13.76 | 1500 | 0.3861 | 0.3509 |
| 0.1046 | 14.68 | 1600 | 0.3798 | 0.3455 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.12.0+cu116
- Datasets 2.7.1
- Tokenizers 0.13.2
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