---
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