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---
base_model: yihongLiu/furina
tags:
- generated_from_trainer
model-index:
- name: furina_seed42_eng_amh_hau_cross_0.0001
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_hau_cross_0.0001
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: 0.0312
- Spearman Corr: 0.7298
## 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: 0.0001
- 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 | 0.52 | 200 | 0.0443 | 0.1783 |
| No log | 1.04 | 400 | 0.0333 | 0.5121 |
| No log | 1.55 | 600 | 0.0424 | 0.5339 |
| 0.0522 | 2.07 | 800 | 0.0398 | 0.5674 |
| 0.0522 | 2.59 | 1000 | 0.0328 | 0.6002 |
| 0.0522 | 3.11 | 1200 | 0.0313 | 0.6285 |
| 0.0522 | 3.63 | 1400 | 0.0292 | 0.6480 |
| 0.0361 | 4.15 | 1600 | 0.0297 | 0.6471 |
| 0.0361 | 4.66 | 1800 | 0.0298 | 0.6724 |
| 0.0361 | 5.18 | 2000 | 0.0308 | 0.7280 |
| 0.0361 | 5.7 | 2200 | 0.0262 | 0.7299 |
| 0.0258 | 6.22 | 2400 | 0.0255 | 0.7406 |
| 0.0258 | 6.74 | 2600 | 0.0284 | 0.7288 |
| 0.0258 | 7.25 | 2800 | 0.0295 | 0.7337 |
| 0.0258 | 7.77 | 3000 | 0.0300 | 0.7393 |
| 0.0164 | 8.29 | 3200 | 0.0271 | 0.7451 |
| 0.0164 | 8.81 | 3400 | 0.0319 | 0.7359 |
| 0.0164 | 9.33 | 3600 | 0.0261 | 0.7314 |
| 0.0164 | 9.84 | 3800 | 0.0290 | 0.7265 |
| 0.0105 | 10.36 | 4000 | 0.0312 | 0.7298 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
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