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: 0.5224
- Accuracy: 0.8
- F1: 0.7972
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-06
- train_batch_size: 16
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 135 | 0.7296 | 0.7292 | 0.6649 |
| No log | 2.0 | 270 | 0.6285 | 0.7875 | 0.7794 |
| No log | 3.0 | 405 | 0.5707 | 0.8 | 0.7931 |
| 0.6461 | 4.0 | 540 | 0.5545 | 0.8 | 0.7936 |
| 0.6461 | 5.0 | 675 | 0.5248 | 0.8125 | 0.8080 |
| 0.6461 | 6.0 | 810 | 0.5166 | 0.8042 | 0.8001 |
| 0.6461 | 7.0 | 945 | 0.5170 | 0.8042 | 0.8093 |
| 0.3513 | 8.0 | 1080 | 0.5179 | 0.8042 | 0.8064 |
| 0.3513 | 9.0 | 1215 | 0.5212 | 0.8 | 0.8006 |
| 0.3513 | 10.0 | 1350 | 0.5224 | 0.8 | 0.7972 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1