---
base_model: yihongLiu/furina
tags:
- generated_from_trainer
model-index:
- name: furina_seed42_eng_kin_hau_basic_2e-05
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# furina_seed42_eng_kin_hau_basic_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: 0.0261
- Spearman Corr: 0.7485

## 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        | 1.59  | 200  | 0.0355          | 0.6099        |
| 0.0837        | 3.19  | 400  | 0.0284          | 0.7050        |
| 0.0265        | 4.78  | 600  | 0.0265          | 0.7290        |
| 0.0202        | 6.37  | 800  | 0.0257          | 0.7317        |
| 0.0153        | 7.97  | 1000 | 0.0252          | 0.7333        |
| 0.0153        | 9.56  | 1200 | 0.0254          | 0.7464        |
| 0.0126        | 11.16 | 1400 | 0.0243          | 0.7483        |
| 0.0109        | 12.75 | 1600 | 0.0254          | 0.7467        |
| 0.009         | 14.34 | 1800 | 0.0253          | 0.7463        |
| 0.0081        | 15.94 | 2000 | 0.0259          | 0.7450        |
| 0.0081        | 17.53 | 2200 | 0.0258          | 0.7454        |
| 0.0072        | 19.12 | 2400 | 0.0249          | 0.7474        |
| 0.0066        | 20.72 | 2600 | 0.0264          | 0.7453        |
| 0.0061        | 22.31 | 2800 | 0.0252          | 0.7463        |
| 0.0057        | 23.9  | 3000 | 0.0261          | 0.7485        |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2