metadata
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- common_voice
metrics:
- wer
model-index:
- name: wav2vec2-large-xls-r-300m-turkish-colab
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice
type: common_voice
config: tr
split: test
args: tr
metrics:
- name: Wer
type: wer
value: 0.6898954703832753
wav2vec2-large-xls-r-300m-turkish-colab
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice dataset. It achieves the following results on the evaluation set:
- Loss: 0.7496
- Wer: 0.6899
- Cer: 0.1611
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: 200
- num_epochs: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 6.2963 | 5.71 | 100 | 3.1890 | 1.0 | 0.9948 |
| 3.044 | 11.43 | 200 | 2.8236 | 1.0 | 0.9855 |
| 1.3443 | 17.14 | 300 | 0.8382 | 0.7962 | 0.2023 |
| 0.3201 | 22.86 | 400 | 0.8201 | 0.7369 | 0.1844 |
| 0.1987 | 28.57 | 500 | 0.7496 | 0.6899 | 0.1611 |
Framework versions
- Transformers 4.31.0
- Pytorch 2.0.1+cu118
- Datasets 1.18.3
- Tokenizers 0.13.3