wav2vec2-large-xls-r-300m-bemba-fds
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the BembaSpeech dataset. It achieves the following results on the evaluation set:
- Loss: 0.3594
- Wer: 0.3838
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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 |
---|---|---|---|---|
2.9961 | 0.67 | 500 | 0.5157 | 0.7133 |
0.5903 | 1.34 | 1000 | 0.3663 | 0.4989 |
0.4804 | 2.02 | 1500 | 0.3547 | 0.4653 |
0.4146 | 2.69 | 2000 | 0.3274 | 0.4345 |
0.3792 | 3.36 | 2500 | 0.3586 | 0.4640 |
0.3509 | 4.03 | 3000 | 0.3360 | 0.4316 |
0.3114 | 4.7 | 3500 | 0.3382 | 0.4303 |
0.2935 | 5.38 | 4000 | 0.3263 | 0.4091 |
0.2723 | 6.05 | 4500 | 0.3348 | 0.4175 |
0.2502 | 6.72 | 5000 | 0.3317 | 0.4147 |
0.2334 | 7.39 | 5500 | 0.3542 | 0.4030 |
0.2287 | 8.06 | 6000 | 0.3594 | 0.4067 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.10.0+cu111
- Datasets 1.13.3
- Tokenizers 0.10.3
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