metadata
base_model: DeepPavlov/rubert-base-cased-conversational
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: rubert-base-cased-conversational_ner-v3
results: []
rubert-base-cased-conversational_ner-v3
This model is a fine-tuned version of DeepPavlov/rubert-base-cased-conversational on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1204
- Precision: 0.7484
- Recall: 0.7987
- F1: 0.7727
- Accuracy: 0.9242
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 | 75 | 0.2186 | 0.4860 | 0.5839 | 0.5305 | 0.8634 |
| No log | 2.0 | 150 | 0.1380 | 0.6886 | 0.7718 | 0.7278 | 0.9200 |
| No log | 3.0 | 225 | 0.1204 | 0.7484 | 0.7987 | 0.7727 | 0.9242 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1
- Datasets 2.14.4
- Tokenizers 0.13.3