|
--- |
|
license: mit |
|
base_model: xlnet-base-cased |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: XLNet-Reddit-Sentiment-Analysis |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# XLNet-Reddit-Sentiment-Analysis |
|
|
|
This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co./xlnet-base-cased) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.7042 |
|
- Rmse: 0.6062 |
|
- Accuracy: 0.8574 |
|
|
|
## 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: 7 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Rmse | Accuracy | |
|
|:-------------:|:-----:|:-----:|:---------------:|:------:|:--------:| |
|
| 0.8318 | 1.0 | 3790 | 0.7042 | 0.6062 | 0.8574 | |
|
| 0.6979 | 2.0 | 7580 | 0.8326 | 0.6754 | 0.8416 | |
|
| 0.7497 | 3.0 | 11370 | 1.0764 | 0.7446 | 0.8004 | |
|
| 0.8444 | 4.0 | 15160 | 0.9529 | 0.6628 | 0.8458 | |
|
| 0.6879 | 5.0 | 18950 | 0.8014 | 0.6442 | 0.8479 | |
|
| 0.5306 | 6.0 | 22740 | 0.7252 | 0.6174 | 0.8627 | |
|
| 0.466 | 7.0 | 26530 | 0.7364 | 0.5965 | 0.8691 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.0.dev0 |
|
- Pytorch 2.0.0 |
|
- Datasets 2.1.0 |
|
- Tokenizers 0.14.1 |
|
|
