metadata
license: mit
base_model: xlnet-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: XLNet-Reddit-Sentiment-Analysis-16-epochs
results: []
XLNet-Reddit-Sentiment-Analysis-16-epochs
This model is a fine-tuned version of xlnet-base-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7667
- Rmse: 0.6675
- Accuracy: 0.8427
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: 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: 9
Training results
| Training Loss | Epoch | Step | Validation Loss | Rmse | Accuracy |
|---|---|---|---|---|---|
| 0.8682 | 1.0 | 3790 | 0.7667 | 0.6675 | 0.8427 |
| 0.736 | 2.0 | 7580 | 0.7681 | 0.6234 | 0.8585 |
| 0.7613 | 3.0 | 11370 | 0.8174 | 0.6668 | 0.8405 |
| 0.9229 | 4.0 | 15160 | 1.2618 | 0.8202 | 0.6568 |
| 1.0546 | 5.0 | 18950 | 1.2372 | 0.7880 | 0.7592 |
| 0.9142 | 6.0 | 22740 | 0.9488 | 0.7339 | 0.8163 |
| 0.8341 | 7.0 | 26530 | 0.8846 | 0.7230 | 0.8194 |
| 0.8028 | 8.0 | 30320 | 0.8510 | 0.7030 | 0.8289 |
| 0.7784 | 9.0 | 34110 | 0.8805 | 0.7060 | 0.8279 |
Framework versions
- Transformers 4.35.0.dev0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.14.1