---
base_model: yihongLiu/furina
tags:
- generated_from_trainer
model-index:
- name: furina_afr_corr_2e-05
  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_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: 0.0229
- Spearman Corr: 0.7729

## 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        | 0.85  | 200  | 0.0390          | 0.6909        |
| No log        | 1.69  | 400  | 0.0283          | 0.7242        |
| 0.0461        | 2.54  | 600  | 0.0245          | 0.7522        |
| 0.0461        | 3.38  | 800  | 0.0219          | 0.7600        |
| 0.0201        | 4.23  | 1000 | 0.0258          | 0.7668        |
| 0.0201        | 5.07  | 1200 | 0.0234          | 0.7754        |
| 0.0201        | 5.92  | 1400 | 0.0250          | 0.7778        |
| 0.0147        | 6.77  | 1600 | 0.0247          | 0.7670        |
| 0.0147        | 7.61  | 1800 | 0.0236          | 0.7767        |
| 0.0112        | 8.46  | 2000 | 0.0213          | 0.7708        |
| 0.0112        | 9.3   | 2200 | 0.0241          | 0.7825        |
| 0.0092        | 10.15 | 2400 | 0.0228          | 0.7786        |
| 0.0092        | 10.99 | 2600 | 0.0220          | 0.7789        |
| 0.0092        | 11.84 | 2800 | 0.0225          | 0.7742        |
| 0.0073        | 12.68 | 3000 | 0.0229          | 0.7742        |
| 0.0073        | 13.53 | 3200 | 0.0241          | 0.7745        |
| 0.0062        | 14.38 | 3400 | 0.0259          | 0.7771        |
| 0.0062        | 15.22 | 3600 | 0.0254          | 0.7768        |
| 0.0055        | 16.07 | 3800 | 0.0229          | 0.7729        |


### Framework versions

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