metadata
library_name: transformers
license: apache-2.0
base_model: HooshvareLab/bert-fa-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: Bert-Sentiment-Fa
results: []
Bert-Sentiment-Fa
This model is a fine-tuned version of HooshvareLab/bert-fa-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1790
- Accuracy: 0.8167
- F1: 0.8174
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: 3e-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: 15
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 68 | 0.6093 | 0.7583 | 0.7592 |
| No log | 2.0 | 136 | 0.5057 | 0.8125 | 0.8093 |
| No log | 3.0 | 204 | 0.5610 | 0.8125 | 0.8172 |
| No log | 4.0 | 272 | 0.7870 | 0.7958 | 0.7862 |
| No log | 5.0 | 340 | 0.8404 | 0.8042 | 0.8105 |
| No log | 6.0 | 408 | 0.8729 | 0.8208 | 0.8256 |
| No log | 7.0 | 476 | 0.9832 | 0.8292 | 0.8322 |
| 0.1891 | 8.0 | 544 | 1.0597 | 0.825 | 0.8288 |
| 0.1891 | 9.0 | 612 | 1.1262 | 0.8208 | 0.8184 |
| 0.1891 | 10.0 | 680 | 1.1224 | 0.8208 | 0.8260 |
| 0.1891 | 11.0 | 748 | 1.1524 | 0.8167 | 0.8188 |
| 0.1891 | 12.0 | 816 | 1.1460 | 0.8042 | 0.8055 |
| 0.1891 | 13.0 | 884 | 1.1633 | 0.8167 | 0.8202 |
| 0.1891 | 14.0 | 952 | 1.1620 | 0.8167 | 0.8177 |
| 0.0077 | 15.0 | 1020 | 1.1790 | 0.8167 | 0.8174 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1