---
base_model: yihongLiu/furina
tags:
- generated_from_trainer
model-index:
- name: furina_latin_original_kin-amh-eng_train_spearman_corr
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# furina_latin_original_kin-amh-eng_train_spearman_corr

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: 0.0314
- Spearman Corr: 0.7391

## 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        | 1.75  | 200  | 0.0347          | 0.6054        |
| 0.0869        | 3.51  | 400  | 0.0244          | 0.7064        |
| 0.0226        | 5.26  | 600  | 0.0236          | 0.7265        |
| 0.0164        | 7.02  | 800  | 0.0271          | 0.7412        |
| 0.0132        | 8.77  | 1000 | 0.0264          | 0.7449        |
| 0.0107        | 10.53 | 1200 | 0.0300          | 0.7453        |
| 0.0087        | 12.28 | 1400 | 0.0314          | 0.7445        |
| 0.0078        | 14.04 | 1600 | 0.0252          | 0.7416        |
| 0.0078        | 15.79 | 1800 | 0.0276          | 0.7428        |
| 0.0067        | 17.54 | 2000 | 0.0312          | 0.7400        |
| 0.0061        | 19.3  | 2200 | 0.0307          | 0.7426        |
| 0.0057        | 21.05 | 2400 | 0.0318          | 0.7400        |
| 0.0053        | 22.81 | 2600 | 0.0326          | 0.7363        |
| 0.0049        | 24.56 | 2800 | 0.0314          | 0.7391        |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2