metadata
library_name: transformers
license: mit
base_model: cointegrated/rubert-tiny2
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: slot_token_classification_model
results: []
slot_token_classification_model
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: 0.4739
- Precision: 0.6455
- Recall: 0.7092
- F1: 0.6758
- Accuracy: 0.8977
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: 16
- eval_batch_size: 16
- 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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.408 | 1.0 | 720 | 0.4998 | 0.6226 | 0.6688 | 0.6449 | 0.8909 |
| 0.3758 | 2.0 | 1440 | 0.4815 | 0.6349 | 0.6868 | 0.6598 | 0.8953 |
| 0.3383 | 3.0 | 2160 | 0.4746 | 0.6405 | 0.7002 | 0.6690 | 0.8958 |
| 0.3278 | 4.0 | 2880 | 0.4733 | 0.6577 | 0.7032 | 0.6797 | 0.8977 |
| 0.3053 | 5.0 | 3600 | 0.4739 | 0.6455 | 0.7092 | 0.6758 | 0.8977 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0