---
base_model: yihongLiu/furina
tags:
- generated_from_trainer
model-index:
- name: furina_seed42_eng_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_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: 0.0170
- Spearman Corr: 0.7981

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------------:|
| 0.0996        | 2.33  | 200  | 0.0152          | 0.7264        |
| 0.0264        | 4.65  | 400  | 0.0147          | 0.7717        |
| 0.0174        | 6.98  | 600  | 0.0151          | 0.7851        |
| 0.0138        | 9.3   | 800  | 0.0145          | 0.7920        |
| 0.0115        | 11.63 | 1000 | 0.0164          | 0.7917        |
| 0.0083        | 13.95 | 1200 | 0.0163          | 0.7924        |
| 0.0077        | 16.28 | 1400 | 0.0168          | 0.7967        |
| 0.0067        | 18.6  | 1600 | 0.0171          | 0.7994        |
| 0.0062        | 20.93 | 1800 | 0.0170          | 0.7984        |
| 0.0058        | 23.26 | 2000 | 0.0175          | 0.8021        |
| 0.0057        | 25.58 | 2200 | 0.0168          | 0.7985        |
| 0.0052        | 27.91 | 2400 | 0.0170          | 0.7981        |


### Framework versions

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