WAXAL-mas-lug-sog-ful-w2v-bert-2.0
This model is a fine-tuned version of facebook/w2v-bert-2.0 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5309
- Cer: 0.0984
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: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Use adamw_torch_fused 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
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Cer |
|---|---|---|---|---|
| 9.2011 | 1.4493 | 300 | 0.7215 | 0.1652 |
| 1.9641 | 2.8986 | 600 | 0.5023 | 0.1236 |
| 1.0306 | 4.3478 | 900 | 0.4635 | 0.1095 |
| 0.7774 | 5.7971 | 1200 | 0.4473 | 0.1066 |
| 0.4446 | 7.2464 | 1500 | 0.4614 | 0.1008 |
| 0.3021 | 8.6957 | 1800 | 0.4922 | 0.1000 |
| 0.3021 | 10.0 | 2070 | 0.5309 | 0.0984 |
Framework versions
- Transformers 5.13.0
- Pytorch 2.13.0+cu130
- Datasets 5.0.0
- Tokenizers 0.22.2