wav2vec2-large-xls-r-300m-Swedish
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: 0.3641
- Wer: 0.2473
- Cer: 0.0758
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 7.5e-05
- train_batch_size: 64
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 50
- mixed_precision_training: Native AMP
Training results
Training Loss |
Epoch |
Step |
Validation Loss |
Wer |
Cer |
6.1097 |
5.49 |
500 |
3.1422 |
1.0 |
1.0 |
2.985 |
10.98 |
1000 |
1.7357 |
0.9876 |
0.4125 |
1.0363 |
16.48 |
1500 |
0.4773 |
0.3510 |
0.1047 |
0.6111 |
21.97 |
2000 |
0.3937 |
0.2998 |
0.0910 |
0.4942 |
27.47 |
2500 |
0.3779 |
0.2776 |
0.0844 |
0.4421 |
32.96 |
3000 |
0.3745 |
0.2630 |
0.0807 |
0.4018 |
38.46 |
3500 |
0.3685 |
0.2553 |
0.0781 |
0.3759 |
43.95 |
4000 |
0.3618 |
0.2488 |
0.0761 |
0.3646 |
49.45 |
4500 |
0.3641 |
0.2473 |
0.0758 |
Framework versions
- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2.dev0
- Tokenizers 0.11.0