|
--- |
|
library_name: transformers |
|
language: |
|
- en |
|
license: apache-2.0 |
|
base_model: google/bert_uncased_L-4_H-512_A-8 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- glue |
|
metrics: |
|
- spearmanr |
|
model-index: |
|
- name: bert_uncased_L-4_H-512_A-8_stsb |
|
results: |
|
- task: |
|
name: Text Classification |
|
type: text-classification |
|
dataset: |
|
name: GLUE STSB |
|
type: glue |
|
args: stsb |
|
metrics: |
|
- name: Spearmanr |
|
type: spearmanr |
|
value: 0.8704339623572931 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# bert_uncased_L-4_H-512_A-8_stsb |
|
|
|
This model is a fine-tuned version of [google/bert_uncased_L-4_H-512_A-8](https://huggingface.co/google/bert_uncased_L-4_H-512_A-8) on the GLUE STSB dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.5646 |
|
- Pearson: 0.8739 |
|
- Spearmanr: 0.8704 |
|
- Combined Score: 0.8721 |
|
|
|
## 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-05 |
|
- train_batch_size: 256 |
|
- eval_batch_size: 256 |
|
- seed: 10 |
|
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
|
- lr_scheduler_type: linear |
|
- num_epochs: 50 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Pearson | Spearmanr | Combined Score | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:| |
|
| 2.5878 | 1.0 | 23 | 0.9754 | 0.7823 | 0.7580 | 0.7702 | |
|
| 0.797 | 2.0 | 46 | 0.7766 | 0.8466 | 0.8482 | 0.8474 | |
|
| 0.5786 | 3.0 | 69 | 0.6314 | 0.8603 | 0.8587 | 0.8595 | |
|
| 0.4961 | 4.0 | 92 | 0.6342 | 0.8643 | 0.8637 | 0.8640 | |
|
| 0.3944 | 5.0 | 115 | 0.6018 | 0.8694 | 0.8683 | 0.8689 | |
|
| 0.3362 | 6.0 | 138 | 0.6101 | 0.8659 | 0.8657 | 0.8658 | |
|
| 0.2932 | 7.0 | 161 | 0.6056 | 0.8678 | 0.8666 | 0.8672 | |
|
| 0.2495 | 8.0 | 184 | 0.6255 | 0.8679 | 0.8672 | 0.8675 | |
|
| 0.2268 | 9.0 | 207 | 0.5970 | 0.8699 | 0.8685 | 0.8692 | |
|
| 0.2037 | 10.0 | 230 | 0.6517 | 0.8691 | 0.8672 | 0.8682 | |
|
| 0.191 | 11.0 | 253 | 0.6017 | 0.8709 | 0.8677 | 0.8693 | |
|
| 0.1678 | 12.0 | 276 | 0.6097 | 0.8704 | 0.8685 | 0.8695 | |
|
| 0.1546 | 13.0 | 299 | 0.6052 | 0.8713 | 0.8701 | 0.8707 | |
|
| 0.1486 | 14.0 | 322 | 0.5914 | 0.8714 | 0.8689 | 0.8701 | |
|
| 0.1372 | 15.0 | 345 | 0.6175 | 0.8738 | 0.8702 | 0.8720 | |
|
| 0.131 | 16.0 | 368 | 0.5826 | 0.8727 | 0.8702 | 0.8715 | |
|
| 0.1216 | 17.0 | 391 | 0.5779 | 0.8717 | 0.8686 | 0.8702 | |
|
| 0.1145 | 18.0 | 414 | 0.5646 | 0.8739 | 0.8704 | 0.8721 | |
|
| 0.1158 | 19.0 | 437 | 0.5811 | 0.8738 | 0.8711 | 0.8724 | |
|
| 0.109 | 20.0 | 460 | 0.5896 | 0.8763 | 0.8720 | 0.8742 | |
|
| 0.105 | 21.0 | 483 | 0.5863 | 0.8737 | 0.8705 | 0.8721 | |
|
| 0.0995 | 22.0 | 506 | 0.5758 | 0.8741 | 0.8701 | 0.8721 | |
|
| 0.0971 | 23.0 | 529 | 0.5781 | 0.8748 | 0.8713 | 0.8731 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.46.3 |
|
- Pytorch 2.2.1+cu118 |
|
- Datasets 2.17.0 |
|
- Tokenizers 0.20.3 |
|
|
