metadata
license: mit
base_model: tangminhanh/ops_tg
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: ops_cate
results: []
ops_cate
This model is a fine-tuned version of tangminhanh/ops_tg on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0637
- Accuracy: 0.7300
- F1: 0.7824
- Precision: 0.8357
- Recall: 0.7355
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: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 7
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 121 | 0.1398 | 0.1661 | 0.2807 | 0.9302 | 0.1653 |
| No log | 2.0 | 242 | 0.1019 | 0.4891 | 0.6180 | 0.8375 | 0.4897 |
| No log | 3.0 | 363 | 0.0805 | 0.6532 | 0.7296 | 0.8234 | 0.6550 |
| No log | 4.0 | 484 | 0.0711 | 0.6854 | 0.7523 | 0.8313 | 0.6870 |
| 0.1434 | 5.0 | 605 | 0.0655 | 0.7072 | 0.7697 | 0.8409 | 0.7097 |
| 0.1434 | 6.0 | 726 | 0.0645 | 0.7227 | 0.7742 | 0.8316 | 0.7242 |
| 0.1434 | 7.0 | 847 | 0.0637 | 0.7300 | 0.7824 | 0.8357 | 0.7355 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1