|
--- |
|
library_name: transformers |
|
language: |
|
- en |
|
license: apache-2.0 |
|
base_model: google/bert_uncased_L-4_H-256_A-4 |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- glue |
|
metrics: |
|
- spearmanr |
|
model-index: |
|
- name: bert_uncased_L-4_H-256_A-4_stsb |
|
results: |
|
- task: |
|
name: Text Classification |
|
type: text-classification |
|
dataset: |
|
name: GLUE STSB |
|
type: glue |
|
args: stsb |
|
metrics: |
|
- name: Spearmanr |
|
type: spearmanr |
|
value: 0.8541619713648296 |
|
--- |
|
|
|
<!-- 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-256_A-4_stsb |
|
|
|
This model is a fine-tuned version of [google/bert_uncased_L-4_H-256_A-4](https://huggingface.co/google/bert_uncased_L-4_H-256_A-4) on the GLUE STSB dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.6283 |
|
- Pearson: 0.8545 |
|
- Spearmanr: 0.8542 |
|
- Combined Score: 0.8543 |
|
|
|
## 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:-------:|:---------:|:--------------:| |
|
| 5.5773 | 1.0 | 23 | 2.7412 | 0.3845 | 0.3343 | 0.3594 | |
|
| 2.5793 | 2.0 | 46 | 1.9158 | 0.7727 | 0.7557 | 0.7642 | |
|
| 1.5767 | 3.0 | 69 | 0.9541 | 0.7706 | 0.7473 | 0.7590 | |
|
| 0.9474 | 4.0 | 92 | 0.7628 | 0.8133 | 0.8070 | 0.8101 | |
|
| 0.7258 | 5.0 | 115 | 0.6785 | 0.8383 | 0.8429 | 0.8406 | |
|
| 0.6162 | 6.0 | 138 | 0.6756 | 0.8436 | 0.8439 | 0.8437 | |
|
| 0.5455 | 7.0 | 161 | 0.6391 | 0.8480 | 0.8504 | 0.8492 | |
|
| 0.4912 | 8.0 | 184 | 0.6582 | 0.8461 | 0.8472 | 0.8466 | |
|
| 0.4443 | 9.0 | 207 | 0.6561 | 0.8472 | 0.8482 | 0.8477 | |
|
| 0.3995 | 10.0 | 230 | 0.6429 | 0.8504 | 0.8503 | 0.8503 | |
|
| 0.3689 | 11.0 | 253 | 0.6283 | 0.8545 | 0.8542 | 0.8543 | |
|
| 0.3418 | 12.0 | 276 | 0.6592 | 0.8520 | 0.8520 | 0.8520 | |
|
| 0.3302 | 13.0 | 299 | 0.6507 | 0.8524 | 0.8530 | 0.8527 | |
|
| 0.319 | 14.0 | 322 | 0.6484 | 0.8528 | 0.8526 | 0.8527 | |
|
| 0.2863 | 15.0 | 345 | 0.6397 | 0.8526 | 0.8527 | 0.8526 | |
|
| 0.2774 | 16.0 | 368 | 0.6379 | 0.8559 | 0.8555 | 0.8557 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.46.3 |
|
- Pytorch 2.2.1+cu118 |
|
- Datasets 2.17.0 |
|
- Tokenizers 0.20.3 |
|
|
