---
base_model: yihongLiu/furina
tags:
- generated_from_trainer
model-index:
- name: furina_seed42_eng_kin_amh_roman
  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_kin_amh_roman

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: 0.0284
- Spearman Corr: 0.7771

## 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        | 0.65  | 200  | 0.0373          | 0.5747        |
| No log        | 1.3   | 400  | 0.0297          | 0.6851        |
| No log        | 1.95  | 600  | 0.0311          | 0.7236        |
| 0.0545        | 2.61  | 800  | 0.0305          | 0.7322        |
| 0.0545        | 3.26  | 1000 | 0.0281          | 0.7496        |
| 0.0545        | 3.91  | 1200 | 0.0278          | 0.7582        |
| 0.0208        | 4.56  | 1400 | 0.0278          | 0.7528        |
| 0.0208        | 5.21  | 1600 | 0.0238          | 0.7556        |
| 0.0208        | 5.86  | 1800 | 0.0235          | 0.7631        |
| 0.0143        | 6.51  | 2000 | 0.0245          | 0.7634        |
| 0.0143        | 7.17  | 2200 | 0.0243          | 0.7619        |
| 0.0143        | 7.82  | 2400 | 0.0242          | 0.7651        |
| 0.0102        | 8.47  | 2600 | 0.0257          | 0.7645        |
| 0.0102        | 9.12  | 2800 | 0.0271          | 0.7713        |
| 0.0102        | 9.77  | 3000 | 0.0255          | 0.7661        |
| 0.0079        | 10.42 | 3200 | 0.0218          | 0.7720        |
| 0.0079        | 11.07 | 3400 | 0.0250          | 0.7658        |
| 0.0079        | 11.73 | 3600 | 0.0266          | 0.7628        |
| 0.0064        | 12.38 | 3800 | 0.0267          | 0.7657        |
| 0.0064        | 13.03 | 4000 | 0.0261          | 0.7680        |
| 0.0064        | 13.68 | 4200 | 0.0232          | 0.7720        |
| 0.0055        | 14.33 | 4400 | 0.0256          | 0.7737        |
| 0.0055        | 14.98 | 4600 | 0.0237          | 0.7736        |
| 0.0055        | 15.64 | 4800 | 0.0284          | 0.7771        |


### Framework versions

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