---
base_model: yihongLiu/furina
tags:
- generated_from_trainer
model-index:
- name: furina_seed42_eng_amh_esp_basic_5e-06
  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_amh_esp_basic_5e-06

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: 0.0213
- Spearman Corr: 0.7510

## 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: 5e-06
- 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        | 1.59  | 200  | 0.0439          | 0.1550        |
| 0.1335        | 3.17  | 400  | 0.0317          | 0.6373        |
| 0.0485        | 4.76  | 600  | 0.0210          | 0.6957        |
| 0.0295        | 6.35  | 800  | 0.0249          | 0.7234        |
| 0.0295        | 7.94  | 1000 | 0.0196          | 0.7301        |
| 0.0243        | 9.52  | 1200 | 0.0195          | 0.7405        |
| 0.0221        | 11.11 | 1400 | 0.0214          | 0.7448        |
| 0.02          | 12.7  | 1600 | 0.0237          | 0.7426        |
| 0.0187        | 14.29 | 1800 | 0.0198          | 0.7470        |
| 0.0187        | 15.87 | 2000 | 0.0208          | 0.7501        |
| 0.0176        | 17.46 | 2200 | 0.0240          | 0.7495        |
| 0.0163        | 19.05 | 2400 | 0.0212          | 0.7518        |
| 0.0158        | 20.63 | 2600 | 0.0237          | 0.7475        |
| 0.0154        | 22.22 | 2800 | 0.0213          | 0.7510        |


### Framework versions

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