| --- |
| library_name: transformers |
| license: mit |
| base_model: xlnet/xlnet-large-cased |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| model-index: |
| - name: sentiment-XLNnet-2025_II |
| 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. --> |
|
|
| # sentiment-XLNnet-2025_II |
| |
| This model is a fine-tuned version of [xlnet/xlnet-large-cased](https://huggingface.co/xlnet/xlnet-large-cased) on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.5971 |
| - F1 Macro: 0.7693 |
| - F1 Weighted: 0.7732 |
| - Accuracy: 0.7721 |
| |
| ## 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: 16 |
| - eval_batch_size: 16 |
| - seed: 42 |
| - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
| - lr_scheduler_type: linear |
| - lr_scheduler_warmup_ratio: 0.1 |
| - num_epochs: 10 |
| - mixed_precision_training: Native AMP |
| |
| ### Training results |
| |
| | Training Loss | Epoch | Step | Validation Loss | F1 Macro | F1 Weighted | Accuracy | |
| |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:| |
| | 0.7148 | 1.0 | 164 | 0.6885 | 0.3818 | 0.3498 | 0.4558 | |
| | 0.6764 | 2.0 | 328 | 0.6087 | 0.6659 | 0.6695 | 0.6677 | |
| | 0.6066 | 3.0 | 492 | 0.5459 | 0.7364 | 0.7459 | 0.7515 | |
| | 0.4872 | 4.0 | 656 | 0.5602 | 0.7572 | 0.7650 | 0.7683 | |
| | 0.386 | 5.0 | 820 | 0.5875 | 0.7701 | 0.7768 | 0.7790 | |
| | 0.2853 | 6.0 | 984 | 0.6121 | 0.7798 | 0.7841 | 0.7835 | |
| | 0.2407 | 7.0 | 1148 | 0.9999 | 0.7620 | 0.7690 | 0.7713 | |
| | 0.1793 | 8.0 | 1312 | 1.1289 | 0.7721 | 0.7786 | 0.7805 | |
| | 0.1414 | 9.0 | 1476 | 1.2392 | 0.7615 | 0.7660 | 0.7652 | |
| |
| |
| ### Framework versions |
| |
| - Transformers 4.57.1 |
| - Pytorch 2.8.0+cu126 |
| - Datasets 4.0.0 |
| - Tokenizers 0.22.1 |
| |
