---
base_model: yihongLiu/furina
tags:
- generated_from_trainer
model-index:
- name: furina_amh_loss_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_amh_loss_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: 0.0237
- Spearman Corr: 0.7697

## 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        | 0.9   | 200  | 0.0232          | 0.7664        |
| No log        | 1.81  | 400  | 0.0228          | 0.7676        |
| 0.0039        | 2.71  | 600  | 0.0255          | 0.7675        |
| 0.0039        | 3.62  | 800  | 0.0235          | 0.7673        |
| 0.0033        | 4.52  | 1000 | 0.0224          | 0.7712        |
| 0.0033        | 5.43  | 1200 | 0.0243          | 0.7666        |
| 0.0039        | 6.33  | 1400 | 0.0223          | 0.7700        |
| 0.0039        | 7.24  | 1600 | 0.0244          | 0.7631        |
| 0.0036        | 8.14  | 1800 | 0.0234          | 0.7705        |
| 0.0036        | 9.05  | 2000 | 0.0224          | 0.7680        |
| 0.0036        | 9.95  | 2200 | 0.0227          | 0.7673        |
| 0.0032        | 10.86 | 2400 | 0.0225          | 0.7680        |
| 0.0032        | 11.76 | 2600 | 0.0242          | 0.7665        |
| 0.0029        | 12.67 | 2800 | 0.0233          | 0.7671        |
| 0.0029        | 13.57 | 3000 | 0.0214          | 0.7683        |
| 0.0027        | 14.48 | 3200 | 0.0217          | 0.7705        |
| 0.0027        | 15.38 | 3400 | 0.0233          | 0.7675        |
| 0.0025        | 16.29 | 3600 | 0.0239          | 0.7683        |
| 0.0025        | 17.19 | 3800 | 0.0231          | 0.7678        |
| 0.0023        | 18.1  | 4000 | 0.0234          | 0.7692        |
| 0.0023        | 19.0  | 4200 | 0.0227          | 0.7674        |
| 0.0023        | 19.91 | 4400 | 0.0230          | 0.7687        |
| 0.0022        | 20.81 | 4600 | 0.0237          | 0.7697        |


### Framework versions

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