metadata
base_model: cointegrated/rubert-tiny2
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: lct-rubert-tiny2-ner
results: []
lct-rubert-tiny2-ner
This model is a fine-tuned version of cointegrated/rubert-tiny2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0270
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.9985
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 | 38 | 0.1353 | 0.0 | 0.0 | 0.0 | 0.9985 |
| No log | 2.0 | 76 | 0.0334 | 0.0 | 0.0 | 0.0 | 0.9985 |
| No log | 3.0 | 114 | 0.0270 | 0.0 | 0.0 | 0.0 | 0.9985 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1
- Datasets 2.19.2
- Tokenizers 0.19.1