---
base_model: yihongLiu/furina
tags:
- generated_from_trainer
model-index:
- name: furina_seed42_eng_kin_hau
  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_seed42_eng_kin_hau

This model is a fine-tuned version of [yihongLiu/furina](https://huggingface.co/yihongLiu/furina) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0202
- Spearman Corr: 0.7925

## 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        | 0.59  | 200  | 0.0427          | 0.4859        |
| No log        | 1.18  | 400  | 0.0345          | 0.6546        |
| No log        | 1.77  | 600  | 0.0295          | 0.6863        |
| 0.0527        | 2.36  | 800  | 0.0272          | 0.6929        |
| 0.0527        | 2.95  | 1000 | 0.0284          | 0.7195        |
| 0.0527        | 3.55  | 1200 | 0.0271          | 0.7192        |
| 0.0244        | 4.14  | 1400 | 0.0253          | 0.7366        |
| 0.0244        | 4.73  | 1600 | 0.0236          | 0.7434        |
| 0.0244        | 5.32  | 1800 | 0.0239          | 0.7436        |
| 0.0244        | 5.91  | 2000 | 0.0255          | 0.7483        |
| 0.017         | 6.5   | 2200 | 0.0230          | 0.7575        |
| 0.017         | 7.09  | 2400 | 0.0231          | 0.7541        |
| 0.017         | 7.68  | 2600 | 0.0230          | 0.7568        |
| 0.0123        | 8.27  | 2800 | 0.0228          | 0.7575        |
| 0.0123        | 8.86  | 3000 | 0.0233          | 0.7633        |
| 0.0123        | 9.45  | 3200 | 0.0228          | 0.7679        |
| 0.0092        | 10.04 | 3400 | 0.0226          | 0.7647        |
| 0.0092        | 10.64 | 3600 | 0.0220          | 0.7704        |
| 0.0092        | 11.23 | 3800 | 0.0214          | 0.7717        |
| 0.0092        | 11.82 | 4000 | 0.0219          | 0.7768        |
| 0.0074        | 12.41 | 4200 | 0.0215          | 0.7760        |
| 0.0074        | 13.0  | 4400 | 0.0209          | 0.7792        |
| 0.0074        | 13.59 | 4600 | 0.0206          | 0.7796        |
| 0.006         | 14.18 | 4800 | 0.0211          | 0.7770        |
| 0.006         | 14.77 | 5000 | 0.0211          | 0.7801        |
| 0.006         | 15.36 | 5200 | 0.0216          | 0.7807        |
| 0.006         | 15.95 | 5400 | 0.0205          | 0.7841        |
| 0.0052        | 16.54 | 5600 | 0.0211          | 0.7846        |
| 0.0052        | 17.13 | 5800 | 0.0206          | 0.7873        |
| 0.0052        | 17.73 | 6000 | 0.0202          | 0.7863        |
| 0.0045        | 18.32 | 6200 | 0.0205          | 0.7858        |
| 0.0045        | 18.91 | 6400 | 0.0202          | 0.7886        |
| 0.0045        | 19.5  | 6600 | 0.0208          | 0.7876        |
| 0.0042        | 20.09 | 6800 | 0.0203          | 0.7902        |
| 0.0042        | 20.68 | 7000 | 0.0211          | 0.7850        |
| 0.0042        | 21.27 | 7200 | 0.0204          | 0.7899        |
| 0.0042        | 21.86 | 7400 | 0.0207          | 0.7905        |
| 0.0037        | 22.45 | 7600 | 0.0202          | 0.7925        |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1