metadata
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
model-index:
- name: Sentiment-Analysis-Model
results: []
Sentiment-Analysis-Model
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6488
- F1 Score: 0.7281
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: 5e-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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Score |
|---|---|---|---|---|
| 0.8011 | 0.5 | 500 | 0.8189 | 0.6563 |
| 0.7437 | 1.0 | 1000 | 0.7877 | 0.6793 |
| 0.6996 | 1.5 | 1500 | 0.6979 | 0.6996 |
| 0.6886 | 2.0 | 2000 | 0.6893 | 0.6910 |
| 0.6384 | 2.5 | 2500 | 0.8285 | 0.7133 |
| 0.6254 | 3.0 | 3000 | 0.6488 | 0.7281 |
| 0.56 | 3.5 | 3500 | 0.6755 | 0.7402 |
| 0.5731 | 4.0 | 4000 | 0.6775 | 0.7456 |
| 0.504 | 4.5 | 4500 | 0.7232 | 0.7407 |
| 0.4839 | 5.0 | 5000 | 0.7219 | 0.7512 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3