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---
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
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