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---
base_model: yihongLiu/furina
tags:
- generated_from_trainer
model-index:
- name: furina_hau_corr_2e-05
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. -->
# furina_hau_corr_2e-05
This model is a fine-tuned version of [yihongLiu/furina](https://huggingface.co/yihongLiu/furina) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0209
- Spearman Corr: 0.7736
## 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: 32
- eval_batch_size: 128
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Spearman Corr |
|:-------------:|:-----:|:----:|:---------------:|:-------------:|
| No log | 0.95 | 200 | 0.0214 | 0.7723 |
| No log | 1.91 | 400 | 0.0225 | 0.7716 |
| 0.0012 | 2.86 | 600 | 0.0211 | 0.7695 |
| 0.0012 | 3.82 | 800 | 0.0207 | 0.7718 |
| 0.0011 | 4.77 | 1000 | 0.0214 | 0.7723 |
| 0.0011 | 5.73 | 1200 | 0.0209 | 0.7753 |
| 0.001 | 6.68 | 1400 | 0.0210 | 0.7710 |
| 0.001 | 7.64 | 1600 | 0.0204 | 0.7721 |
| 0.0009 | 8.59 | 1800 | 0.0217 | 0.7731 |
| 0.0009 | 9.55 | 2000 | 0.0216 | 0.7692 |
| 0.0009 | 10.5 | 2200 | 0.0206 | 0.7724 |
| 0.0009 | 11.46 | 2400 | 0.0213 | 0.7734 |
| 0.0009 | 12.41 | 2600 | 0.0208 | 0.7725 |
| 0.0009 | 13.37 | 2800 | 0.0207 | 0.7760 |
| 0.0008 | 14.32 | 3000 | 0.0209 | 0.7724 |
| 0.0008 | 15.27 | 3200 | 0.0208 | 0.7729 |
| 0.0007 | 16.23 | 3400 | 0.0212 | 0.7732 |
| 0.0007 | 17.18 | 3600 | 0.0209 | 0.7746 |
| 0.0007 | 18.14 | 3800 | 0.0209 | 0.7745 |
| 0.0007 | 19.09 | 4000 | 0.0202 | 0.7759 |
| 0.0007 | 20.05 | 4200 | 0.0206 | 0.7750 |
| 0.0007 | 21.0 | 4400 | 0.0209 | 0.7736 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
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