---
base_model: yihongLiu/furina
tags:
- generated_from_trainer
model-index:
- name: furina_ary_loss_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_ary_loss_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: 0.0226
- Spearman Corr: 0.7565

## 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        | 0.9   | 200  | 0.0228          | 0.7563        |
| No log        | 1.8   | 400  | 0.0235          | 0.7560        |
| 0.0036        | 2.7   | 600  | 0.0225          | 0.7529        |
| 0.0036        | 3.6   | 800  | 0.0230          | 0.7605        |
| 0.0035        | 4.5   | 1000 | 0.0219          | 0.7584        |
| 0.0035        | 5.41  | 1200 | 0.0227          | 0.7586        |
| 0.0034        | 6.31  | 1400 | 0.0221          | 0.7607        |
| 0.0034        | 7.21  | 1600 | 0.0225          | 0.7612        |
| 0.0038        | 8.11  | 1800 | 0.0219          | 0.7575        |
| 0.0038        | 9.01  | 2000 | 0.0224          | 0.7576        |
| 0.0038        | 9.91  | 2200 | 0.0220          | 0.7598        |
| 0.0043        | 10.81 | 2400 | 0.0224          | 0.7601        |
| 0.0043        | 11.71 | 2600 | 0.0226          | 0.7565        |


### Framework versions

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