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rubert-base-massive-ner
This model is a fine-tuned version of DeepPavlov/rubert-base-cased on the massive dataset. It achieves the following results on the evaluation set:
- Loss: 0.0367
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.1228 | 0.77 | 500 | 0.0565 |
| 0.0517 | 1.54 | 1000 | 0.0367 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
