|
--- |
|
base_model: yihongLiu/furina |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: furina_seed42_eng_kin_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_kin_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: 0.0490 |
|
- Spearman Corr: nan |
|
|
|
## 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 | 0.53 | 200 | 0.0493 | 0.0550 | |
|
| No log | 1.06 | 400 | 0.0495 | 0.0857 | |
|
| No log | 1.6 | 600 | 0.0491 | -0.0146 | |
|
| 0.0593 | 2.13 | 800 | 0.0491 | 0.0012 | |
|
| 0.0593 | 2.66 | 1000 | 0.0496 | 0.0851 | |
|
| 0.0593 | 3.19 | 1200 | 0.0493 | 0.0390 | |
|
| 0.0593 | 3.72 | 1400 | 0.0490 | 0.1463 | |
|
| 0.055 | 4.26 | 1600 | 0.0491 | 0.0244 | |
|
| 0.055 | 4.79 | 1800 | 0.0491 | nan | |
|
| 0.055 | 5.32 | 2000 | 0.0491 | nan | |
|
| 0.055 | 5.85 | 2200 | 0.0494 | nan | |
|
| 0.0541 | 6.38 | 2400 | 0.0493 | nan | |
|
| 0.0541 | 6.91 | 2600 | 0.0491 | -0.0093 | |
|
| 0.0541 | 7.45 | 2800 | 0.0490 | nan | |
|
| 0.0541 | 7.98 | 3000 | 0.0490 | nan | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.37.2 |
|
- Pytorch 2.1.0+cu121 |
|
- Datasets 2.17.0 |
|
- Tokenizers 0.15.2 |
|
|
