metadata
library_name: transformers
base_model: DeepPavlov/rubert-base-cased-conversational
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: bert_ner_output
results: []
bert_ner_output
This model is a fine-tuned version of DeepPavlov/rubert-base-cased-conversational on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0114
- Precision: 0.9004
- Recall: 0.9049
- F1: 0.9026
- Accuracy: 0.9972
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: 32
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.0038 | 1.0 | 6119 | 0.0109 | 0.8962 | 0.9070 | 0.9016 | 0.9972 |
| 0.0193 | 2.0 | 12238 | 0.0114 | 0.9004 | 0.9049 | 0.9026 | 0.9972 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Datasets 3.1.0
- Tokenizers 0.20.3