---
base_model: yihongLiu/furina
tags:
- generated_from_trainer
model-index:
- name: furina_seed42_eng_amh_hau_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_hau_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: 0.0270
- Spearman Corr: 0.7754

## 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        | 1.55  | 200  | 0.0668          | 0.0276        |
| 0.1596        | 3.1   | 400  | 0.0398          | 0.4309        |
| 0.0561        | 4.65  | 600  | 0.0270          | 0.7038        |
| 0.0335        | 6.2   | 800  | 0.0272          | 0.7202        |
| 0.0335        | 7.75  | 1000 | 0.0223          | 0.7452        |
| 0.0281        | 9.3   | 1200 | 0.0226          | 0.7406        |
| 0.0249        | 10.85 | 1400 | 0.0265          | 0.7632        |
| 0.022         | 12.4  | 1600 | 0.0222          | 0.7669        |
| 0.0205        | 13.95 | 1800 | 0.0231          | 0.7678        |
| 0.0205        | 15.5  | 2000 | 0.0228          | 0.7705        |
| 0.0191        | 17.05 | 2200 | 0.0251          | 0.7765        |
| 0.0184        | 18.6  | 2400 | 0.0224          | 0.7784        |
| 0.0173        | 20.16 | 2600 | 0.0270          | 0.7754        |


### Framework versions

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