metadata
license: mit
base_model: gpt2
tags:
- generated_from_trainer
datasets:
- bigbench
metrics:
- accuracy
model-index:
- name: bigbench_entailedpolarity-gpt2
results:
- task:
name: Text Classification
type: text-classification
dataset:
name: bigbench
type: bigbench
config: entailed_polarity
split: train
args: entailed_polarity
metrics:
- name: Accuracy
type: accuracy
value: 0.9166666666666666
bigbench_entailedpolarity-gpt2
This model is a fine-tuned version of gpt2 on the bigbench dataset. It achieves the following results on the evaluation set:
- Loss: 1.0213
- Accuracy: 0.9167
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 |
|---|---|---|---|---|
| No log | 1.0 | 24 | 0.5201 | 0.875 |
| No log | 2.0 | 48 | 0.3512 | 0.875 |
| No log | 3.0 | 72 | 0.4245 | 0.8333 |
| No log | 4.0 | 96 | 0.3220 | 0.9167 |
| No log | 5.0 | 120 | 0.3962 | 0.875 |
| No log | 6.0 | 144 | 0.5551 | 0.875 |
| No log | 7.0 | 168 | 0.8597 | 0.875 |
| No log | 8.0 | 192 | 0.4610 | 0.9583 |
| No log | 9.0 | 216 | 0.9003 | 0.9167 |
| No log | 10.0 | 240 | 0.8778 | 0.9167 |
| No log | 11.0 | 264 | 0.9036 | 0.9167 |
| No log | 12.0 | 288 | 0.9188 | 0.9167 |
| No log | 13.0 | 312 | 1.0192 | 0.9167 |
| No log | 14.0 | 336 | 0.9984 | 0.9167 |
| No log | 15.0 | 360 | 0.9718 | 0.9167 |
| No log | 16.0 | 384 | 0.9882 | 0.9167 |
| No log | 17.0 | 408 | 1.0189 | 0.9167 |
| No log | 18.0 | 432 | 1.0210 | 0.9167 |
| No log | 19.0 | 456 | 1.0211 | 0.9167 |
| No log | 20.0 | 480 | 1.0213 | 0.9167 |
Framework versions
- Transformers 4.35.2
- Pytorch 1.10.1+cu102
- Datasets 2.15.0
- Tokenizers 0.15.0