w2v-bert-2.0-test
This model is a fine-tuned version of facebook/w2v-bert-2.0 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2815
- Wer: 0.2494
- Cer: 0.0627
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: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- 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: 5.0
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
---|---|---|---|---|---|
0.8172 | 1.0 | 1473 | 0.3534 | 0.3020 | 0.0763 |
0.2395 | 2.0 | 2946 | 0.2995 | 0.2780 | 0.0701 |
0.1948 | 3.0 | 4419 | 0.2876 | 0.2576 | 0.0649 |
0.1665 | 4.0 | 5892 | 0.2886 | 0.2583 | 0.0640 |
0.1462 | 5.0 | 7365 | 0.2815 | 0.2494 | 0.0627 |
Framework versions
- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1
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facebook/w2v-bert-2.0