w2v-bert-2.0-bemgen-male-model
This model is a fine-tuned version of facebook/w2v-bert-2.0 on the BEMGEN - BEM dataset. It achieves the following results on the evaluation set:
- Loss: 0.3124
- Wer: 0.4801
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: 4
- eval_batch_size: 4
- 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_steps: 500
- training_steps: 3000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
No log | 0.1034 | 100 | 0.9843 | 0.9557 |
No log | 0.2068 | 200 | 0.9218 | 0.9166 |
No log | 0.3102 | 300 | 0.9675 | 0.9435 |
No log | 0.4137 | 400 | 1.1171 | 0.9413 |
1.1866 | 0.5171 | 500 | 1.0130 | 0.9430 |
1.1866 | 0.6205 | 600 | 0.9595 | 1.0711 |
1.1866 | 0.7239 | 700 | 0.8301 | 0.8833 |
1.1866 | 0.8273 | 800 | 0.8072 | 0.8745 |
1.1866 | 0.9307 | 900 | 0.7413 | 0.8407 |
0.7779 | 1.0341 | 1000 | 0.6572 | 0.7763 |
0.7779 | 1.1375 | 1100 | 0.6588 | 0.7513 |
0.7779 | 1.2410 | 1200 | 0.5933 | 0.7642 |
0.7779 | 1.3444 | 1300 | 0.5910 | 0.7305 |
0.7779 | 1.4478 | 1400 | 0.5967 | 0.7584 |
0.5649 | 1.5512 | 1500 | 0.5757 | 0.7299 |
0.5649 | 1.6546 | 1600 | 0.5121 | 0.6682 |
0.5649 | 1.7580 | 1700 | 0.5339 | 0.6576 |
0.5649 | 1.8614 | 1800 | 0.4539 | 0.6172 |
0.5649 | 1.9648 | 1900 | 0.4375 | 0.5837 |
0.4839 | 2.0683 | 2000 | 0.4384 | 0.6114 |
0.4839 | 2.1717 | 2100 | 0.3993 | 0.5685 |
0.4839 | 2.2751 | 2200 | 0.4016 | 0.5947 |
0.4839 | 2.3785 | 2300 | 0.3897 | 0.5646 |
0.4839 | 2.4819 | 2400 | 0.3798 | 0.5631 |
0.3288 | 2.5853 | 2500 | 0.3543 | 0.5203 |
0.3288 | 2.6887 | 2600 | 0.3427 | 0.5156 |
0.3288 | 2.7921 | 2700 | 0.3382 | 0.5109 |
0.3288 | 2.8956 | 2800 | 0.3257 | 0.4982 |
0.3288 | 2.9990 | 2900 | 0.3133 | 0.4790 |
0.2666 | 3.1024 | 3000 | 0.3124 | 0.4797 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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facebook/w2v-bert-2.0