w2v-bert-2.0-Chinese-colab-CV16.0-aishell-ark-gs-vtb-new_tokenizer
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: 1.2200
- Wer: 1.7271
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: 4
- seed: 42
- gradient_accumulation_steps: 64
- total_train_batch_size: 256
- 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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 5.059 | 0.9976 | 156 | 1.4359 | 1.7492 |
| 2.9898 | 1.9912 | 312 | 1.3586 | 1.8124 |
| 2.17 | 2.9848 | 468 | 1.2909 | 1.7153 |
| 1.9683 | 3.9784 | 624 | 1.2440 | 1.7769 |
| 1.6888 | 4.9720 | 780 | 1.2200 | 1.7271 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.5.1+cu121
- Datasets 2.17.1
- Tokenizers 0.21.0
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Base model
facebook/w2v-bert-2.0