metadata
library_name: transformers
license: mit
base_model: xlnet/xlnet-large-cased
tags:
- generated_from_trainer
model-index:
- name: cs221-xlnet-large-cased-finetuned
results: []
cs221-xlnet-large-cased-finetuned
This model is a fine-tuned version of xlnet/xlnet-large-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5884
- Bce Loss: 0.5884
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: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Bce Loss |
|---|---|---|---|---|
| 0.5902 | 1.0 | 139 | 0.5891 | 0.5891 |
| 0.5564 | 2.0 | 278 | 0.5912 | 0.5912 |
| 0.5744 | 3.0 | 417 | 0.5889 | 0.5889 |
| 0.5504 | 4.0 | 556 | 0.5884 | 0.5884 |
Framework versions
- Transformers 4.47.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.21.0