metadata
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
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: 0.7000
- Accuracy: 0.7165
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 | Accuracy |
|---|---|---|---|---|
| 0.8648 | 0.5 | 500 | 0.9848 | 0.703 |
| 0.8367 | 1.0 | 1000 | 0.8764 | 0.683 |
| 0.7815 | 1.5 | 1500 | 0.7792 | 0.7145 |
| 0.7751 | 2.0 | 2000 | 0.7516 | 0.7095 |
| 0.8081 | 2.5 | 2500 | 0.7783 | 0.7055 |
| 0.8142 | 3.0 | 3000 | 0.8125 | 0.688 |
| 0.8497 | 3.5 | 3500 | 0.8383 | 0.6575 |
| 0.8006 | 4.0 | 4000 | 0.7412 | 0.705 |
| 0.7363 | 4.5 | 4500 | 0.7299 | 0.718 |
| 0.7151 | 5.0 | 5000 | 0.7000 | 0.7165 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3