metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- super_glue
metrics:
- rouge
model-index:
- name: T5_finetuned
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: super_glue
type: super_glue
config: boolq
split: train
args: boolq
metrics:
- name: Rouge1
type: rouge
value: 79.3272
T5_finetuned
This model is a fine-tuned version of t5-base on the super_glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.1077
- Rouge1: 79.3272
- Rouge2: 0.0
- Rougel: 79.2966
- Rougelsum: 79.3272
- Gen Len: 2.8269
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 0.5134 | 1.0 | 590 | 0.1102 | 79.8165 | 0.0 | 79.8165 | 79.8471 | 2.7713 |
| 0.105 | 2.0 | 1180 | 0.1049 | 80.3364 | 0.0 | 80.3364 | 80.367 | 2.6483 |
| 0.1023 | 3.0 | 1770 | 0.1077 | 79.3272 | 0.0 | 79.2966 | 79.3272 | 2.8269 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.0+cu116
- Datasets 2.8.0
- Tokenizers 0.13.2