|
--- |
|
license: apache-2.0 |
|
base_model: bert-base-uncased |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- super_glue |
|
metrics: |
|
- accuracy |
|
model-index: |
|
- name: superglue_rte-bert-base-uncased |
|
results: |
|
- task: |
|
name: Text Classification |
|
type: text-classification |
|
dataset: |
|
name: super_glue |
|
type: super_glue |
|
config: rte |
|
split: validation |
|
args: rte |
|
metrics: |
|
- name: Accuracy |
|
type: accuracy |
|
value: 0.6739130434782609 |
|
--- |
|
|
|
<!-- 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. --> |
|
|
|
# superglue_rte-bert-base-uncased |
|
|
|
This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the super_glue dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.5070 |
|
- Accuracy: 0.6739 |
|
|
|
## 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: 4 |
|
- eval_batch_size: 32 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 20 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
|
|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
|
| 0.704 | 1.0 | 623 | 0.6653 | 0.6159 | |
|
| 0.6848 | 2.0 | 1246 | 0.7144 | 0.4203 | |
|
| 0.7083 | 3.0 | 1869 | 0.6922 | 0.5797 | |
|
| 0.7014 | 4.0 | 2492 | 0.7327 | 0.6232 | |
|
| 0.6528 | 5.0 | 3115 | 0.6727 | 0.6522 | |
|
| 0.6471 | 6.0 | 3738 | 0.8413 | 0.6159 | |
|
| 0.5872 | 7.0 | 4361 | 0.8780 | 0.5507 | |
|
| 0.5954 | 8.0 | 4984 | 0.7604 | 0.6377 | |
|
| 0.5566 | 9.0 | 5607 | 0.8578 | 0.6812 | |
|
| 0.5576 | 10.0 | 6230 | 2.0498 | 0.5362 | |
|
| 0.4923 | 11.0 | 6853 | 1.4097 | 0.6304 | |
|
| 0.5688 | 12.0 | 7476 | 1.4146 | 0.6667 | |
|
| 0.433 | 13.0 | 8099 | 1.3354 | 0.6594 | |
|
| 0.4259 | 14.0 | 8722 | 1.3271 | 0.6957 | |
|
| 0.3869 | 15.0 | 9345 | 1.2881 | 0.6812 | |
|
| 0.3641 | 16.0 | 9968 | 1.4485 | 0.6739 | |
|
| 0.3292 | 17.0 | 10591 | 1.3445 | 0.6739 | |
|
| 0.3734 | 18.0 | 11214 | 1.4917 | 0.6739 | |
|
| 0.3227 | 19.0 | 11837 | 1.5281 | 0.6739 | |
|
| 0.3133 | 20.0 | 12460 | 1.5070 | 0.6739 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.32.1 |
|
- Pytorch 1.13.0+cu117 |
|
- Datasets 2.15.0 |
|
- Tokenizers 0.13.3 |
|
|
