|
--- |
|
license: mit |
|
base_model: xlnet-base-cased |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- tweet_sentiment_multilingual |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: xlnet-finetuned-socialmediatweet |
|
results: |
|
- task: |
|
name: Text Classification |
|
type: text-classification |
|
dataset: |
|
name: tweet_sentiment_multilingual |
|
type: tweet_sentiment_multilingual |
|
config: english |
|
split: validation |
|
args: english |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.7129629850387573 |
|
--- |
|
|
|
<!-- 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-finetuned-socialmediatweet |
|
|
|
This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on the tweet_sentiment_multilingual dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 2.6923 |
|
- Accuracy: 0.7130 |
|
|
|
## 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: 2e-05 |
|
- train_batch_size: 32 |
|
- eval_batch_size: 32 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 20 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:--------:| |
|
| 0.0161 | 1.0 | 58 | 2.4538 | 0.6821 | |
|
| 0.0416 | 2.0 | 116 | 2.3751 | 0.6821 | |
|
| 0.0294 | 3.0 | 174 | 2.4929 | 0.7068 | |
|
| 0.031 | 4.0 | 232 | 2.5655 | 0.7037 | |
|
| 0.0422 | 5.0 | 290 | 3.0881 | 0.6605 | |
|
| 0.0751 | 6.0 | 348 | 2.6787 | 0.6883 | |
|
| 0.0264 | 7.0 | 406 | 2.5283 | 0.7006 | |
|
| 0.0123 | 8.0 | 464 | 2.5634 | 0.7006 | |
|
| 0.0277 | 9.0 | 522 | 2.7127 | 0.6852 | |
|
| 0.0448 | 10.0 | 580 | 2.6113 | 0.6759 | |
|
| 0.0261 | 11.0 | 638 | 2.6640 | 0.6759 | |
|
| 0.0111 | 12.0 | 696 | 2.6089 | 0.6914 | |
|
| 0.0239 | 13.0 | 754 | 2.5785 | 0.6975 | |
|
| 0.0255 | 14.0 | 812 | 2.6923 | 0.7130 | |
|
| 0.0242 | 15.0 | 870 | 2.4704 | 0.7068 | |
|
| 0.0131 | 16.0 | 928 | 2.6724 | 0.6667 | |
|
| 0.0059 | 17.0 | 986 | 2.5554 | 0.7068 | |
|
| 0.0066 | 18.0 | 1044 | 2.6696 | 0.6698 | |
|
| 0.001 | 19.0 | 1102 | 2.5653 | 0.6883 | |
|
| 0.0026 | 20.0 | 1160 | 2.5846 | 0.6883 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.2 |
|
- Pytorch 2.1.0+cu118 |
|
- Datasets 2.15.0 |
|
- Tokenizers 0.15.0 |
|
|
