wav2vec2-large-xls-r-1b-bemba-fds
This model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on the BembaSpeech dataset. It achieves the following results on the evaluation set:
- Loss: 0.2898
- Wer: 0.3435
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: 5e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 15
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
1.7986 | 0.34 | 500 | 0.4549 | 0.7292 |
0.5358 | 0.67 | 1000 | 0.3325 | 0.4491 |
0.4559 | 1.01 | 1500 | 0.3090 | 0.3954 |
0.3983 | 1.35 | 2000 | 0.3067 | 0.4105 |
0.4067 | 1.68 | 2500 | 0.2838 | 0.3678 |
0.3722 | 2.02 | 3000 | 0.2824 | 0.3762 |
0.3286 | 2.36 | 3500 | 0.2810 | 0.3670 |
0.3239 | 2.69 | 4000 | 0.2643 | 0.3501 |
0.3187 | 3.03 | 4500 | 0.2838 | 0.3754 |
0.2801 | 3.36 | 5000 | 0.2815 | 0.3507 |
0.2806 | 3.7 | 5500 | 0.2725 | 0.3486 |
0.2714 | 4.04 | 6000 | 0.2898 | 0.3435 |
Framework versions
- Transformers 4.16.2
- Pytorch 1.10.0+cu111
- Datasets 1.18.3
- Tokenizers 0.11.0
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