metadata
library_name: transformers
license: mit
base_model: xlnet-large-cased
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: CS221-xlnet-large-cased-finetuned-semeval-NT
results: []
CS221-xlnet-large-cased-finetuned-semeval-NT
This model is a fine-tuned version of xlnet-large-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3954
- F1: 0.7622
- Roc Auc: 0.8208
- Accuracy: 0.4657
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 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 |
|---|---|---|---|---|---|---|
| 0.5664 | 1.0 | 139 | 0.5827 | 0.4593 | 0.6262 | 0.1516 |
| 0.5686 | 2.0 | 278 | 0.5801 | 0.4593 | 0.6262 | 0.1516 |
| 0.478 | 3.0 | 417 | 0.4532 | 0.6704 | 0.7544 | 0.3249 |
| 0.3799 | 4.0 | 556 | 0.3867 | 0.7262 | 0.7929 | 0.4079 |
| 0.2727 | 5.0 | 695 | 0.3954 | 0.7622 | 0.8208 | 0.4657 |
| 0.1747 | 6.0 | 834 | 0.3805 | 0.7403 | 0.8009 | 0.4603 |
| 0.11 | 7.0 | 973 | 0.4434 | 0.7565 | 0.8164 | 0.4386 |
| 0.0705 | 8.0 | 1112 | 0.4957 | 0.7619 | 0.8196 | 0.4549 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0