metadata
license: apache-2.0
base_model: ai-forever/ruBert-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: ruBert-base-finetuned-pos
results: []
ruBert-base-finetuned-pos
This model is a fine-tuned version of ai-forever/ruBert-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1544
- Precision: 0.8561
- Recall: 0.8723
- F1: 0.8642
- Accuracy: 0.8822
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 311 | 0.1686 | 0.8380 | 0.8440 | 0.8410 | 0.8565 |
| 0.0464 | 2.0 | 622 | 0.1597 | 0.8462 | 0.8582 | 0.8521 | 0.8715 |
| 0.0464 | 3.0 | 933 | 0.1544 | 0.8561 | 0.8723 | 0.8642 | 0.8822 |
| 0.0046 | 4.0 | 1244 | 0.1564 | 0.8469 | 0.8629 | 0.8548 | 0.8737 |
| 0.0029 | 5.0 | 1555 | 0.1556 | 0.8538 | 0.8700 | 0.8618 | 0.8801 |
Framework versions
- Transformers 4.39.0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2