metadata
license: mit
base_model: gpt2
tags:
- generated_from_trainer
datasets:
- super_glue
metrics:
- accuracy
model-index:
- name: superglue_rte-gpt2
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: 0.5434782608695652
superglue_rte-gpt2
This model is a fine-tuned version of gpt2 on the super_glue dataset. It achieves the following results on the evaluation set:
- Loss: 4.4821
- Accuracy: 0.5435
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 |
|---|---|---|---|---|
| 0.778 | 1.0 | 623 | 0.6845 | 0.5797 |
| 0.7042 | 2.0 | 1246 | 0.6909 | 0.5797 |
| 0.7022 | 3.0 | 1869 | 0.6608 | 0.5507 |
| 0.7145 | 4.0 | 2492 | 0.7206 | 0.5797 |
| 0.6183 | 5.0 | 3115 | 0.8510 | 0.5435 |
| 0.5855 | 6.0 | 3738 | 1.7010 | 0.5362 |
| 0.5468 | 7.0 | 4361 | 2.3186 | 0.5362 |
| 0.4411 | 8.0 | 4984 | 2.6790 | 0.5435 |
| 0.3226 | 9.0 | 5607 | 2.6486 | 0.5507 |
| 0.2479 | 10.0 | 6230 | 3.2958 | 0.5362 |
| 0.1632 | 11.0 | 6853 | 3.3893 | 0.5290 |
| 0.1526 | 12.0 | 7476 | 3.2382 | 0.5942 |
| 0.1127 | 13.0 | 8099 | 4.0889 | 0.4855 |
| 0.0902 | 14.0 | 8722 | 3.7049 | 0.5580 |
| 0.0997 | 15.0 | 9345 | 3.6377 | 0.5290 |
| 0.083 | 16.0 | 9968 | 3.6723 | 0.6087 |
| 0.0612 | 17.0 | 10591 | 4.2905 | 0.5870 |
| 0.0357 | 18.0 | 11214 | 4.4611 | 0.5145 |
| 0.0643 | 19.0 | 11837 | 4.4033 | 0.5217 |
| 0.0348 | 20.0 | 12460 | 4.4821 | 0.5435 |
Framework versions
- Transformers 4.32.1
- Pytorch 1.13.0+cu117
- Datasets 2.15.0
- Tokenizers 0.13.3