metadata
license: mit
base_model: xlnet-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: XLNet-Reddit-Sentiment-Analysis
results: []
XLNet-Reddit-Sentiment-Analysis
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: 0.7135
- Rmse: 0.6123
- Accuracy: 0.8691
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Rmse | Accuracy |
|---|---|---|---|---|---|
| 0.8907 | 1.0 | 3790 | 0.9401 | 0.6715 | 0.8152 |
| 0.7855 | 2.0 | 7580 | 0.7974 | 0.6301 | 0.8501 |
| 0.6837 | 3.0 | 11370 | 0.8520 | 0.6384 | 0.8553 |
| 0.6271 | 4.0 | 15160 | 0.7731 | 0.6140 | 0.8669 |
| 0.5311 | 5.0 | 18950 | 0.7135 | 0.6123 | 0.8691 |
Framework versions
- Transformers 4.35.0.dev0
- Pytorch 2.0.0
- Datasets 2.1.0
- Tokenizers 0.14.1