sberbank-rubert-base-collection3
This model is a fine-tuned version of sberbank-ai/ruBert-base on the collection3 dataset. It achieves the following results on the validation set:
- Loss: 0.0772
- Precision: 0.9380
- Recall: 0.9594
- F1: 0.9486
- Accuracy: 0.9860
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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 0.1
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0899 | 1.0 | 2326 | 0.0760 | 0.9040 | 0.9330 | 0.9182 | 0.9787 |
| 0.0522 | 2.0 | 4652 | 0.0680 | 0.9330 | 0.9339 | 0.9335 | 0.9821 |
| 0.0259 | 3.0 | 6978 | 0.0745 | 0.9308 | 0.9512 | 0.9409 | 0.9838 |
| 0.0114 | 4.0 | 9304 | 0.0731 | 0.9372 | 0.9573 | 0.9471 | 0.9857 |
| 0.0027 | 5.0 | 11630 | 0.0772 | 0.9380 | 0.9594 | 0.9486 | 0.9860 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.7.0
- Datasets 2.10.1
- Tokenizers 0.13.2