---
base_model: yihongLiu/furina
tags:
- generated_from_trainer
model-index:
- name: furina_seed42_eng_esp_kin_basic_0.0001
  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_0.0001

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: 0.0241
- Spearman Corr: 0.7044

## 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: 0.0001
- 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        | 1.63  | 200  | 0.0289          | 0.5423        |
| 0.0612        | 3.27  | 400  | 0.0263          | 0.6520        |
| 0.0244        | 4.9   | 600  | 0.0236          | 0.6983        |
| 0.0157        | 6.53  | 800  | 0.0229          | 0.7032        |
| 0.011         | 8.16  | 1000 | 0.0244          | 0.6980        |
| 0.011         | 9.8   | 1200 | 0.0275          | 0.7093        |
| 0.0075        | 11.43 | 1400 | 0.0241          | 0.7221        |
| 0.0055        | 13.06 | 1600 | 0.0265          | 0.7163        |
| 0.004         | 14.69 | 1800 | 0.0246          | 0.7128        |
| 0.0036        | 16.33 | 2000 | 0.0242          | 0.7084        |
| 0.0036        | 17.96 | 2200 | 0.0276          | 0.7070        |
| 0.003         | 19.59 | 2400 | 0.0241          | 0.7044        |


### Framework versions

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