|
|
--- |
|
|
library_name: transformers |
|
|
license: mit |
|
|
base_model: xlnet/xlnet-large-cased |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
model-index: |
|
|
- name: cs221-xlnet-large-cased-finetuned |
|
|
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-large-cased-finetuned |
|
|
|
|
|
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: 0.5884 |
|
|
- 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 |
|
|
|
