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---
base_model: yihongLiu/furina
tags:
- generated_from_trainer
model-index:
- name: furina_afr_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_afr_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: 0.0229
- Spearman Corr: 0.7729
## 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 | 0.85 | 200 | 0.0390 | 0.6909 |
| No log | 1.69 | 400 | 0.0283 | 0.7242 |
| 0.0461 | 2.54 | 600 | 0.0245 | 0.7522 |
| 0.0461 | 3.38 | 800 | 0.0219 | 0.7600 |
| 0.0201 | 4.23 | 1000 | 0.0258 | 0.7668 |
| 0.0201 | 5.07 | 1200 | 0.0234 | 0.7754 |
| 0.0201 | 5.92 | 1400 | 0.0250 | 0.7778 |
| 0.0147 | 6.77 | 1600 | 0.0247 | 0.7670 |
| 0.0147 | 7.61 | 1800 | 0.0236 | 0.7767 |
| 0.0112 | 8.46 | 2000 | 0.0213 | 0.7708 |
| 0.0112 | 9.3 | 2200 | 0.0241 | 0.7825 |
| 0.0092 | 10.15 | 2400 | 0.0228 | 0.7786 |
| 0.0092 | 10.99 | 2600 | 0.0220 | 0.7789 |
| 0.0092 | 11.84 | 2800 | 0.0225 | 0.7742 |
| 0.0073 | 12.68 | 3000 | 0.0229 | 0.7742 |
| 0.0073 | 13.53 | 3200 | 0.0241 | 0.7745 |
| 0.0062 | 14.38 | 3400 | 0.0259 | 0.7771 |
| 0.0062 | 15.22 | 3600 | 0.0254 | 0.7768 |
| 0.0055 | 16.07 | 3800 | 0.0229 | 0.7729 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
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