ruBert-base-finetuned-pos
This model was finetuned from ai-forever/ruBert-base on the disk0dancer/ru_sentances_pos dataset. All docs and code can be found on Github.
It achieves the following results on the evaluation set:
- eval_loss: 0.1544
- eval_precision: 0.8561
- eval_recall: 0.8723
- eval_f1: 0.8642
- eval_accuracy: 0.8822
- eval_runtime: 0.2476
- eval_samples_per_second: 80.775
- eval_steps_per_second: 8.078
- step: 0
Model description
Bert + Dence + Softmax + Dropout
Training and evaluation data
Model Trained for Token Classification
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: 5
Framework versions
- Transformers 4.39.0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
- Downloads last month
- 9