---
base_model: yihongLiu/furina
tags:
- generated_from_trainer
model-index:
- name: furina_afr_corr_5e-06
  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_5e-06

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: 0.0213
- Spearman Corr: 0.7660

## 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: 5e-06
- 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  | 0.0813          | 0.0483        |
| No log        | 1.69  | 400  | 0.0439          | 0.3738        |
| 0.1125        | 2.54  | 600  | 0.0360          | 0.6162        |
| 0.1125        | 3.38  | 800  | 0.0287          | 0.6660        |
| 0.035         | 4.23  | 1000 | 0.0271          | 0.6987        |
| 0.035         | 5.07  | 1200 | 0.0248          | 0.7139        |
| 0.035         | 5.92  | 1400 | 0.0252          | 0.7230        |
| 0.026         | 6.77  | 1600 | 0.0246          | 0.7173        |
| 0.026         | 7.61  | 1800 | 0.0230          | 0.7344        |
| 0.0227        | 8.46  | 2000 | 0.0236          | 0.7361        |
| 0.0227        | 9.3   | 2200 | 0.0223          | 0.7470        |
| 0.0203        | 10.15 | 2400 | 0.0227          | 0.7462        |
| 0.0203        | 10.99 | 2600 | 0.0224          | 0.7477        |
| 0.0203        | 11.84 | 2800 | 0.0242          | 0.7483        |
| 0.0186        | 12.68 | 3000 | 0.0218          | 0.7537        |
| 0.0186        | 13.53 | 3200 | 0.0229          | 0.7528        |
| 0.0175        | 14.38 | 3400 | 0.0227          | 0.7552        |
| 0.0175        | 15.22 | 3600 | 0.0221          | 0.7602        |
| 0.0163        | 16.07 | 3800 | 0.0216          | 0.7612        |
| 0.0163        | 16.91 | 4000 | 0.0216          | 0.7619        |
| 0.0163        | 17.76 | 4200 | 0.0217          | 0.7616        |
| 0.0154        | 18.6  | 4400 | 0.0215          | 0.7612        |
| 0.0154        | 19.45 | 4600 | 0.0212          | 0.7651        |
| 0.0146        | 20.3  | 4800 | 0.0216          | 0.7634        |
| 0.0146        | 21.14 | 5000 | 0.0213          | 0.7641        |
| 0.0141        | 21.99 | 5200 | 0.0223          | 0.7629        |
| 0.0141        | 22.83 | 5400 | 0.0213          | 0.7664        |
| 0.0141        | 23.68 | 5600 | 0.0214          | 0.7635        |
| 0.0134        | 24.52 | 5800 | 0.0214          | 0.7649        |
| 0.0134        | 25.37 | 6000 | 0.0216          | 0.7637        |
| 0.013         | 26.22 | 6200 | 0.0214          | 0.7644        |
| 0.013         | 27.06 | 6400 | 0.0213          | 0.7656        |
| 0.013         | 27.91 | 6600 | 0.0214          | 0.7661        |
| 0.0127        | 28.75 | 6800 | 0.0212          | 0.7655        |
| 0.0127        | 29.6  | 7000 | 0.0213          | 0.7660        |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2