wav2vec2-xls-r-300m-FL-af-1hr-v3
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.0397
- Wer: 0.4997
- 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: 0.0001
- 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: 60
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
---|---|---|---|---|---|
10.726 | 2.6316 | 100 | 4.8546 | 1.0 | 1.0 |
3.892 | 5.2632 | 200 | 3.2785 | 1.0 | 1.0 |
3.0342 | 7.8947 | 300 | 2.8899 | 1.0 | 1.0 |
2.8665 | 10.5263 | 400 | 2.8735 | 1.0 | 1.0 |
2.8427 | 13.1579 | 500 | 2.8842 | 1.0 | 1.0 |
2.8293 | 15.7895 | 600 | 2.8202 | 1.0 | 0.9911 |
2.2253 | 18.4211 | 700 | 1.4009 | 0.8946 | 0.4027 |
0.7951 | 21.0526 | 800 | 0.9228 | 0.6411 | 0.2026 |
0.3831 | 23.6842 | 900 | 0.9069 | 0.5647 | 0.1782 |
0.2542 | 26.3158 | 1000 | 0.9096 | 0.5582 | 0.1730 |
0.1801 | 28.9474 | 1100 | 0.9426 | 0.5682 | 0.1725 |
0.1446 | 31.5789 | 1200 | 0.9889 | 0.5349 | 0.1666 |
0.1238 | 34.2105 | 1300 | 0.9938 | 0.5356 | 0.1644 |
0.1068 | 36.8421 | 1400 | 1.0244 | 0.5294 | 0.1647 |
0.1019 | 39.4737 | 1500 | 1.0253 | 0.5151 | 0.1609 |
0.0823 | 42.1053 | 1600 | 1.0374 | 0.5195 | 0.1612 |
0.0769 | 44.7368 | 1700 | 1.0574 | 0.5174 | 0.1600 |
0.0694 | 47.3684 | 1800 | 1.0425 | 0.5119 | 0.1569 |
0.0672 | 50.0 | 1900 | 1.0317 | 0.5054 | 0.1555 |
0.0563 | 52.6316 | 2000 | 1.0554 | 0.5036 | 0.1551 |
0.0541 | 55.2632 | 2100 | 1.0385 | 0.4992 | 0.1529 |
0.0505 | 57.8947 | 2200 | 1.0424 | 0.5003 | 0.1532 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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