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---
library_name: transformers
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: cs221-xlnet-base-cased-finetuned-20-epochs
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. -->
# cs221-xlnet-base-cased-finetuned-20-epochs
This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6676
- F1: 0.7323
- Roc Auc: 0.8005
- Accuracy: 0.4422
## 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: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.0327 | 1.0 | 139 | 0.6538 | 0.7090 | 0.7827 | 0.4224 |
| 0.0168 | 2.0 | 278 | 0.6723 | 0.7309 | 0.8001 | 0.4206 |
| 0.0192 | 3.0 | 417 | 0.6676 | 0.7323 | 0.8005 | 0.4422 |
### Framework versions
- Transformers 4.47.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.21.0
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