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faiq-wav2vec2-large-xlsr-indo-demo-p100
This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the common_voice_11_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.4061
- Wer: 0.4310
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 |
|---|---|---|---|---|
| 5.0742 | 2.92 | 400 | 2.7922 | 1.0 |
| 1.387 | 5.84 | 800 | 0.4667 | 0.6304 |
| 0.3911 | 8.76 | 1200 | 0.4164 | 0.5444 |
| 0.2684 | 11.68 | 1600 | 0.3925 | 0.4910 |
| 0.2165 | 14.6 | 2000 | 0.3962 | 0.4764 |
| 0.1701 | 17.52 | 2400 | 0.4028 | 0.4606 |
| 0.1553 | 20.44 | 2800 | 0.4031 | 0.4511 |
| 0.131 | 23.36 | 3200 | 0.4137 | 0.4443 |
| 0.1191 | 26.28 | 3600 | 0.4001 | 0.4346 |
| 0.108 | 29.2 | 4000 | 0.4061 | 0.4310 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.0.0+cu118
- Datasets 2.6.1
- Tokenizers 0.13.3
