---
base_model: yihongLiu/furina
tags:
- generated_from_trainer
model-index:
- name: furina_seed42_eng_kin_amh
  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_amh

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: 0.0191
- Spearman Corr: 0.7822

## 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        | 0.65  | 200  | 0.0386          | 0.5856        |
| No log        | 1.3   | 400  | 0.0256          | 0.6781        |
| No log        | 1.95  | 600  | 0.0236          | 0.7129        |
| 0.0506        | 2.61  | 800  | 0.0225          | 0.7250        |
| 0.0506        | 3.26  | 1000 | 0.0225          | 0.7343        |
| 0.0506        | 3.91  | 1200 | 0.0215          | 0.7338        |
| 0.022         | 4.56  | 1400 | 0.0210          | 0.7492        |
| 0.022         | 5.21  | 1600 | 0.0219          | 0.7512        |
| 0.022         | 5.86  | 1800 | 0.0199          | 0.7600        |
| 0.016         | 6.51  | 2000 | 0.0209          | 0.7623        |
| 0.016         | 7.17  | 2200 | 0.0201          | 0.7579        |
| 0.016         | 7.82  | 2400 | 0.0203          | 0.7589        |
| 0.0115        | 8.47  | 2600 | 0.0204          | 0.7604        |
| 0.0115        | 9.12  | 2800 | 0.0201          | 0.7655        |
| 0.0115        | 9.77  | 3000 | 0.0201          | 0.7647        |
| 0.0089        | 10.42 | 3200 | 0.0195          | 0.7652        |
| 0.0089        | 11.07 | 3400 | 0.0191          | 0.7728        |
| 0.0089        | 11.73 | 3600 | 0.0197          | 0.7685        |
| 0.0072        | 12.38 | 3800 | 0.0190          | 0.7709        |
| 0.0072        | 13.03 | 4000 | 0.0192          | 0.7707        |
| 0.0072        | 13.68 | 4200 | 0.0189          | 0.7734        |
| 0.006         | 14.33 | 4400 | 0.0193          | 0.7743        |
| 0.006         | 14.98 | 4600 | 0.0191          | 0.7756        |
| 0.006         | 15.64 | 4800 | 0.0189          | 0.7757        |
| 0.0051        | 16.29 | 5000 | 0.0193          | 0.7733        |
| 0.0051        | 16.94 | 5200 | 0.0189          | 0.7796        |
| 0.0051        | 17.59 | 5400 | 0.0185          | 0.7810        |
| 0.0046        | 18.24 | 5600 | 0.0194          | 0.7781        |
| 0.0046        | 18.89 | 5800 | 0.0191          | 0.7787        |
| 0.0046        | 19.54 | 6000 | 0.0186          | 0.7789        |
| 0.0041        | 20.2  | 6200 | 0.0188          | 0.7798        |
| 0.0041        | 20.85 | 6400 | 0.0189          | 0.7796        |
| 0.0041        | 21.5  | 6600 | 0.0187          | 0.7797        |
| 0.0037        | 22.15 | 6800 | 0.0189          | 0.7787        |
| 0.0037        | 22.8  | 7000 | 0.0191          | 0.7822        |


### Framework versions

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