---
base_model: yihongLiu/furina
tags:
- generated_from_trainer
model-index:
- name: furina_seed42_eng_esp_kin_basic
  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_esp_kin_basic

This model is a fine-tuned version of [yihongLiu/furina](https://huggingface.co/yihongLiu/furina) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0183
- Spearman Corr: 0.7765

## 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        | 1.81  | 200  | 0.0242          | 0.6836        |
| 0.0889        | 3.62  | 400  | 0.0204          | 0.7530        |
| 0.025         | 5.43  | 600  | 0.0197          | 0.7779        |
| 0.019         | 7.24  | 800  | 0.0179          | 0.7805        |
| 0.0153        | 9.05  | 1000 | 0.0177          | 0.7877        |
| 0.0121        | 10.86 | 1200 | 0.0170          | 0.7842        |
| 0.0102        | 12.67 | 1400 | 0.0175          | 0.7797        |
| 0.0087        | 14.48 | 1600 | 0.0177          | 0.7753        |
| 0.0077        | 16.29 | 1800 | 0.0172          | 0.7800        |
| 0.007         | 18.1  | 2000 | 0.0175          | 0.7792        |
| 0.0063        | 19.91 | 2200 | 0.0176          | 0.7791        |
| 0.0063        | 21.72 | 2400 | 0.0175          | 0.7754        |
| 0.0057        | 23.53 | 2600 | 0.0175          | 0.7791        |
| 0.0055        | 25.34 | 2800 | 0.0183          | 0.7765        |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1