metadata
base_model: ai-forever/ruRoberta-large
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: ruRoberta-large_ner
results: []
ruRoberta-large_ner
This model is a fine-tuned version of ai-forever/ruRoberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0824
- Precision: 0.7879
- Recall: 0.8667
- F1: 0.8254
- Accuracy: 0.9667
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 15 | 0.2732 | 0.5833 | 0.7 | 0.6364 | 0.88 |
| No log | 2.0 | 30 | 0.1424 | 0.7059 | 0.8 | 0.7500 | 0.94 |
| No log | 3.0 | 45 | 0.0824 | 0.7879 | 0.8667 | 0.8254 | 0.9667 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.1.0.dev20230621+cu117
- Datasets 2.13.0
- Tokenizers 0.13.3