wav2vec2-xls-r-300m-gl-CV8
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: 0.2151
- Wer: 0.2080
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: 0.0001
- 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: 300
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
4.9427 | 4.9 | 500 | 2.8801 | 1.0 |
2.1594 | 9.8 | 1000 | 0.4092 | 0.4001 |
0.7332 | 14.71 | 1500 | 0.2151 | 0.2080 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.10.0+cu111
- Datasets 1.18.1
- Tokenizers 0.10.3
- Downloads last month
- 1
Inference Providers
NEW
This model is not currently available via any of the supported third-party Inference Providers, and
the model is not deployed on the HF Inference API.
Dataset used to train emre/wav2vec2-xls-r-300m-gl-CV8
Evaluation results
- Test WER on Common Voice glself-reported0.208
- Test WER on Common Voice 8.0self-reported22.940
- Test WER on Robust Speech Event - Dev Dataself-reported47.820
- Test WER on Robust Speech Event - Test Dataself-reported50.800