metadata
base_model: ai-forever/ruBert-large
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: ruBert-large_ner
results: []
ruBert-large_ner
This model is a fine-tuned version of ai-forever/ruBert-large on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5158
- Precision: 0.8832
- Recall: 0.9014
- F1: 0.8912
- Accuracy: 0.9234
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: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 438 | 0.3216 | 0.8700 | 0.8309 | 0.8448 | 0.8941 |
| 0.3915 | 2.0 | 876 | 0.3379 | 0.8596 | 0.8790 | 0.8672 | 0.9089 |
| 0.175 | 3.0 | 1314 | 0.3441 | 0.8656 | 0.8833 | 0.8737 | 0.9092 |
| 0.0942 | 4.0 | 1752 | 0.3751 | 0.8651 | 0.8856 | 0.8729 | 0.9104 |
| 0.0597 | 5.0 | 2190 | 0.3919 | 0.8881 | 0.9002 | 0.8935 | 0.9236 |
| 0.0309 | 6.0 | 2628 | 0.4360 | 0.8730 | 0.8958 | 0.8821 | 0.9171 |
| 0.0154 | 7.0 | 3066 | 0.4564 | 0.8848 | 0.8985 | 0.8907 | 0.9234 |
| 0.0064 | 8.0 | 3504 | 0.4809 | 0.8797 | 0.9036 | 0.8904 | 0.9236 |
| 0.0064 | 9.0 | 3942 | 0.5027 | 0.8832 | 0.9024 | 0.8917 | 0.9232 |
| 0.0024 | 10.0 | 4380 | 0.5158 | 0.8832 | 0.9014 | 0.8912 | 0.9234 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1