---
base_model: yihongLiu/furina
tags:
- generated_from_trainer
model-index:
- name: furina_seed42_eng_amh_esp_basic
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# furina_seed42_eng_amh_esp_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: 0.0215
- Spearman Corr: 0.7964

## 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        | 1.76  | 200  | 0.0220          | 0.7121        |
| 0.0794        | 3.52  | 400  | 0.0219          | 0.7836        |
| 0.0236        | 5.29  | 600  | 0.0310          | 0.7932        |
| 0.0176        | 7.05  | 800  | 0.0201          | 0.7950        |
| 0.0136        | 8.81  | 1000 | 0.0218          | 0.7973        |
| 0.0113        | 10.57 | 1200 | 0.0211          | 0.7975        |
| 0.0097        | 12.33 | 1400 | 0.0238          | 0.7996        |
| 0.008         | 14.1  | 1600 | 0.0228          | 0.8032        |
| 0.008         | 15.86 | 1800 | 0.0239          | 0.8028        |
| 0.0071        | 17.62 | 2000 | 0.0232          | 0.8007        |
| 0.0063        | 19.38 | 2200 | 0.0224          | 0.7948        |
| 0.0058        | 21.15 | 2400 | 0.0215          | 0.7964        |


### Framework versions

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