wav2vec2-xls-r-asheshi-akan-5-hours
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.3649
- Wer: 0.2890
- Cer: 0.1532
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: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
Training results
Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
---|---|---|---|---|---|
6.9205 | 5.6818 | 500 | 3.1754 | 1.0 | 1.0 |
3.0873 | 11.3636 | 1000 | 2.8653 | 1.0 | 1.0 |
1.4627 | 17.0455 | 1500 | 1.0507 | 0.4057 | 0.2008 |
0.4223 | 22.7273 | 2000 | 1.0953 | 0.3260 | 0.1708 |
0.2799 | 28.4091 | 2500 | 1.1691 | 0.3063 | 0.1633 |
0.2197 | 34.0909 | 3000 | 1.3488 | 0.3014 | 0.1655 |
0.1707 | 39.7727 | 3500 | 1.3593 | 0.2932 | 0.1566 |
0.1454 | 45.4545 | 4000 | 1.3649 | 0.2890 | 0.1532 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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Base model
facebook/wav2vec2-xls-r-300m