metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
metrics:
- wer
model-index:
- name: wav2vec2-large-xlsr-turkish
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice
type: common_voice
config: tr
split: train+validation
args: tr
metrics:
- name: Wer
type: wer
value: 0.48268818302522726
wav2vec2-large-xlsr-turkish
This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the common_voice dataset. It achieves the following results on the evaluation set:
- Loss: 0.4242
- Wer: 0.4827
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
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 5.0376 | 4.26 | 400 | 2.3690 | 1.0020 |
| 0.7983 | 8.51 | 800 | 0.4755 | 0.6328 |
| 0.3157 | 12.77 | 1200 | 0.4051 | 0.5408 |
| 0.2197 | 17.02 | 1600 | 0.4156 | 0.5149 |
| 0.1643 | 21.28 | 2000 | 0.4286 | 0.5036 |
| 0.1305 | 25.53 | 2400 | 0.4247 | 0.4908 |
| 0.1178 | 29.79 | 2800 | 0.4242 | 0.4827 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2