metadata
language:
- tr
license: cc-by-nc-4.0
tags:
- automatic-speech-recognition
- common_voice
- generated_from_trainer
- mms
datasets:
- common_voice
metrics:
- wer
model-index:
- name: wav2vec2-common_voice-tr-mms-demo-3
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: 0.2267388417934838
wav2vec2-common_voice-tr-mms-demo
This model is a fine-tuned version of facebook/mms-1b-all on the COMMON_VOICE - TR dataset. It achieves the following results on the evaluation set:
- Loss: 0.1532
- Wer: 0.2267
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: 0.001
- train_batch_size: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 4.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| No log | 0.92 | 100 | 0.1822 | 0.2605 |
| No log | 1.83 | 200 | 0.1620 | 0.2389 |
| No log | 2.75 | 300 | 0.1581 | 0.2318 |
| No log | 3.67 | 400 | 0.1535 | 0.2270 |
Framework versions
- Transformers 4.31.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3