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---
library_name: transformers
license: mit
base_model: charisgao/wnc-pretrain
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: side-info-model-output
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. -->
# side-info-model-output
This model is a fine-tuned version of [charisgao/wnc-pretrain](https://huggingface.co/charisgao/wnc-pretrain) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7365
- Precision: 0.8178
- Recall: 0.92
- F1: 0.8659
- Accuracy: 0.8167
## 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: 8
- eval_batch_size: 8
- 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: linear
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.5017 | 0.8547 | 100 | 0.4694 | 0.8304 | 0.9118 | 0.8692 | 0.8194 |
| 0.3786 | 1.7094 | 200 | 0.4741 | 0.7875 | 0.9265 | 0.8514 | 0.7871 |
| 0.253 | 2.5641 | 300 | 0.7509 | 0.8087 | 0.9118 | 0.8571 | 0.8 |
### Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
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