metadata
base_model: ai-forever/ruBert-large
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: bert-chn-classifier
results: []
bert-chn-classifier
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: 0.2343
- Accuracy: 0.9595
- Precision: 0.9595
- Recall: 0.9595
- F1: 0.9595
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
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 0.2249 | 1.0 | 4381 | 0.1770 | 0.9513 | 0.9513 | 0.9513 | 0.9513 |
| 0.1078 | 2.0 | 8762 | 0.1951 | 0.9571 | 0.9571 | 0.9571 | 0.9571 |
| 0.0234 | 3.0 | 13143 | 0.2343 | 0.9595 | 0.9595 | 0.9595 | 0.9595 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1