---
base_model: yihongLiu/furina
tags:
- generated_from_trainer
model-index:
- name: furina_kin_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_kin_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: 0.0215
- Spearman Corr: 0.7702

## 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        | 0.89  | 200  | 0.0217          | 0.7655        |
| No log        | 1.78  | 400  | 0.0210          | 0.7692        |
| 0.0023        | 2.67  | 600  | 0.0215          | 0.7681        |
| 0.0023        | 3.56  | 800  | 0.0214          | 0.7704        |
| 0.0022        | 4.45  | 1000 | 0.0216          | 0.7710        |
| 0.0022        | 5.35  | 1200 | 0.0215          | 0.7693        |
| 0.0021        | 6.24  | 1400 | 0.0217          | 0.7670        |
| 0.0021        | 7.13  | 1600 | 0.0217          | 0.7665        |
| 0.002         | 8.02  | 1800 | 0.0209          | 0.7673        |
| 0.002         | 8.91  | 2000 | 0.0215          | 0.7694        |
| 0.002         | 9.8   | 2200 | 0.0212          | 0.7709        |
| 0.002         | 10.69 | 2400 | 0.0218          | 0.7674        |
| 0.002         | 11.58 | 2600 | 0.0215          | 0.7702        |


### Framework versions

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