File size: 2,516 Bytes
b402ac0 |
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 |
---
base_model: yihongLiu/furina
tags:
- generated_from_trainer
model-index:
- name: furina_hin_loss_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_hin_loss_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: 0.0480
- 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 | 0.85 | 200 | 0.0476 | nan |
| No log | 1.69 | 400 | 0.0476 | nan |
| 0.0476 | 2.54 | 600 | 0.0481 | nan |
| 0.0476 | 3.38 | 800 | 0.0470 | nan |
| 0.0478 | 4.23 | 1000 | 0.0473 | nan |
| 0.0478 | 5.07 | 1200 | 0.0474 | 0.0168 |
| 0.0478 | 5.92 | 1400 | 0.0478 | -0.0241 |
| 0.0479 | 6.77 | 1600 | 0.0478 | nan |
| 0.0479 | 7.61 | 1800 | 0.0466 | nan |
| 0.048 | 8.46 | 2000 | 0.0480 | nan |
| 0.048 | 9.3 | 2200 | 0.0469 | nan |
| 0.0478 | 10.15 | 2400 | 0.0491 | nan |
| 0.0478 | 10.99 | 2600 | 0.0468 | nan |
| 0.0478 | 11.84 | 2800 | 0.0486 | nan |
| 0.0476 | 12.68 | 3000 | 0.0470 | nan |
| 0.0476 | 13.53 | 3200 | 0.0487 | nan |
| 0.0478 | 14.38 | 3400 | 0.0480 | nan |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
|