w2v-bert-2.0-Chinese-colab-CV16.0-aishell-ark-gs-vtb-ts-fs
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: 0.6568
- Wer: 0.9998
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: 128
- total_train_batch_size: 512
- 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: 3
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
1.658 | 0.9981 | 180 | 0.7483 | 1.0 |
1.2313 | 1.9925 | 360 | 0.6796 | 0.9998 |
1.0232 | 2.9870 | 540 | 0.6568 | 0.9998 |
Framework versions
- Transformers 4.49.0
- Pytorch 2.5.1+cu121
- Datasets 2.17.1
- Tokenizers 0.21.0
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Model tree for urarik/w2v-bert-2.0-Chinese-colab-CV16.0-aishell-ark-gs-vtb-ts-fs
Base model
facebook/w2v-bert-2.0