cs221-CS221-xlnet-large-cased-finetuned-semeval-finetuned-20-epochs
This model is a fine-tuned version of Kuongan/CS221-xlnet-large-cased-finetuned-semeval on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1168
- F1: 0.9527
- Roc Auc: 0.9608
- Accuracy: 0.8953
Model description
More information needed
Intended uses & limitations
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Training and evaluation data
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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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 20
Training results
Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
---|---|---|---|---|---|---|
0.0972 | 1.0 | 64 | 0.1168 | 0.9527 | 0.9608 | 0.8953 |
0.083 | 2.0 | 128 | 0.1284 | 0.9508 | 0.9616 | 0.8913 |
0.0483 | 3.0 | 192 | 0.1371 | 0.9474 | 0.9598 | 0.8874 |
0.029 | 4.0 | 256 | 0.1419 | 0.9484 | 0.9595 | 0.8854 |
0.0208 | 5.0 | 320 | 0.1778 | 0.9440 | 0.9575 | 0.8814 |
0.0106 | 6.0 | 384 | 0.1570 | 0.9477 | 0.9613 | 0.8794 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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Model tree for sercetexam9/cs221-CS221-xlnet-large-cased-finetuned-semeval-finetuned-20-epochs
Base model
xlnet/xlnet-large-cased