File size: 2,717 Bytes
aa13424 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 |
---
base_model: yihongLiu/furina
tags:
- generated_from_trainer
model-index:
- name: furina_ind_loss_2e-05
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_ind_loss_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: 0.0202
- Spearman Corr: 0.7740
## 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 | 0.85 | 200 | 0.0209 | 0.7711 |
| No log | 1.69 | 400 | 0.0213 | 0.7712 |
| 0.0009 | 2.54 | 600 | 0.0219 | 0.7735 |
| 0.0009 | 3.38 | 800 | 0.0209 | 0.7734 |
| 0.0006 | 4.23 | 1000 | 0.0207 | 0.7711 |
| 0.0006 | 5.07 | 1200 | 0.0209 | 0.7714 |
| 0.0006 | 5.92 | 1400 | 0.0215 | 0.7696 |
| 0.0005 | 6.77 | 1600 | 0.0215 | 0.7714 |
| 0.0005 | 7.61 | 1800 | 0.0209 | 0.7724 |
| 0.0005 | 8.46 | 2000 | 0.0204 | 0.7735 |
| 0.0005 | 9.3 | 2200 | 0.0207 | 0.7746 |
| 0.0007 | 10.15 | 2400 | 0.0202 | 0.7756 |
| 0.0007 | 10.99 | 2600 | 0.0209 | 0.7742 |
| 0.0007 | 11.84 | 2800 | 0.0205 | 0.7750 |
| 0.0007 | 12.68 | 3000 | 0.0203 | 0.7743 |
| 0.0007 | 13.53 | 3200 | 0.0207 | 0.7730 |
| 0.0007 | 14.38 | 3400 | 0.0209 | 0.7736 |
| 0.0007 | 15.22 | 3600 | 0.0205 | 0.7751 |
| 0.0006 | 16.07 | 3800 | 0.0206 | 0.7735 |
| 0.0006 | 16.91 | 4000 | 0.0202 | 0.7740 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
|