---
base_model: yihongLiu/furina
tags:
- generated_from_trainer
model-index:
- name: furina_seed42_eng_kin_amh_latin_2e-05
  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_kin_amh_latin_2e-05

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: 0.0242
- Spearman Corr: 0.7470

## 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  | 0.0281          | 0.6376        |
| 0.0807        | 3.51  | 400  | 0.0246          | 0.7176        |
| 0.0216        | 5.26  | 600  | 0.0249          | 0.7301        |
| 0.0153        | 7.02  | 800  | 0.0226          | 0.7384        |
| 0.0119        | 8.77  | 1000 | 0.0236          | 0.7484        |
| 0.0096        | 10.53 | 1200 | 0.0247          | 0.7425        |
| 0.0079        | 12.28 | 1400 | 0.0226          | 0.7424        |
| 0.0068        | 14.04 | 1600 | 0.0236          | 0.7499        |
| 0.0068        | 15.79 | 1800 | 0.0235          | 0.7482        |
| 0.006         | 17.54 | 2000 | 0.0256          | 0.7489        |
| 0.0054        | 19.3  | 2200 | 0.0240          | 0.7489        |
| 0.005         | 21.05 | 2400 | 0.0242          | 0.7470        |


### Framework versions

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