Mandarin_naive
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: 0.4584
- Wer: 0.3999
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
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
4.8963 | 3.67 | 400 | 1.0645 | 0.8783 |
0.5506 | 7.34 | 800 | 0.5032 | 0.5389 |
0.2111 | 11.01 | 1200 | 0.4765 | 0.4712 |
0.1336 | 14.68 | 1600 | 0.4815 | 0.4511 |
0.0974 | 18.35 | 2000 | 0.4956 | 0.4370 |
0.0748 | 22.02 | 2400 | 0.4881 | 0.4235 |
0.0584 | 25.69 | 2800 | 0.4732 | 0.4193 |
0.0458 | 29.36 | 3200 | 0.4584 | 0.3999 |
Framework versions
- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0
- Downloads last month
- 16
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.