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library_name: transformers
license: mit
base_model: xlnet/xlnet-base-cased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: XLNetHateSpeechClassification
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. -->
# XLNetHateSpeechClassification
This model is a fine-tuned version of [xlnet/xlnet-base-cased](https://huggingface.co/xlnet/xlnet-base-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4902
- Accuracy: 0.8253
## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7005 | 1.0 | 1137 | 0.6925 | 0.5198 |
| 0.7039 | 2.0 | 2274 | 0.6949 | 0.4802 |
| 0.7015 | 3.0 | 3411 | 0.6863 | 0.6264 |
| 0.5107 | 4.0 | 4548 | 0.4807 | 0.7769 |
| 0.4288 | 5.0 | 5685 | 0.5123 | 0.8088 |
| 0.3948 | 6.0 | 6822 | 0.4936 | 0.8275 |
| 0.3481 | 7.0 | 7959 | 0.4902 | 0.8253 |
### Framework versions
- Transformers 4.48.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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