---
base_model: yihongLiu/furina
tags:
- generated_from_trainer
model-index:
- name: furina_seed42_eng_esp_hau_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_hau_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: 0.0312
- Spearman Corr: 0.7194

## 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        | 1.45  | 200  | 0.0282          | 0.6099        |
| 0.0652        | 2.91  | 400  | 0.0303          | 0.6702        |
| 0.0263        | 4.36  | 600  | 0.0301          | 0.7175        |
| 0.0263        | 5.82  | 800  | 0.0333          | 0.7147        |
| 0.0178        | 7.27  | 1000 | 0.0346          | 0.7279        |
| 0.0123        | 8.73  | 1200 | 0.0274          | 0.7307        |
| 0.0089        | 10.18 | 1400 | 0.0290          | 0.7331        |
| 0.0089        | 11.64 | 1600 | 0.0302          | 0.7243        |
| 0.0064        | 13.09 | 1800 | 0.0292          | 0.7243        |
| 0.0052        | 14.55 | 2000 | 0.0297          | 0.7253        |
| 0.0044        | 16.0  | 2200 | 0.0335          | 0.7158        |
| 0.0044        | 17.45 | 2400 | 0.0313          | 0.7319        |
| 0.0038        | 18.91 | 2600 | 0.0289          | 0.7169        |
| 0.0032        | 20.36 | 2800 | 0.0312          | 0.7194        |


### Framework versions

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