metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- squad
metrics:
- rouge
model_index:
- name: t5-small-finetuned-xsum-2
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: squad
type: squad
args: plain_text
metric:
name: Rouge1
type: rouge
value: 28.8137
t5-small-finetuned-xsum-2
This model is a fine-tuned version of t5-small on the squad dataset. It achieves the following results on the evaluation set:
- Loss: 1.9536
- Rouge1: 28.8137
- Rouge2: 9.1265
- Rougel: 26.0238
- Rougelsum: 26.0217
- Gen Len: 13.854
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: 10
- eval_batch_size: 10
- 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 |
|---|---|---|---|---|---|---|---|---|
| 2.2142 | 1.0 | 8760 | 1.9994 | 29.007 | 9.2583 | 26.2377 | 26.2356 | 13.4546 |
| 2.1372 | 2.0 | 17520 | 1.9622 | 29.1077 | 9.445 | 26.3734 | 26.3687 | 13.6995 |
| 2.0755 | 3.0 | 26280 | 1.9536 | 28.8137 | 9.1265 | 26.0238 | 26.0217 | 13.854 |
Framework versions
- Transformers 4.9.2
- Pytorch 1.9.0+cu102
- Datasets 1.11.0
- Tokenizers 0.10.3