20% of the training data
license: apache-2.0 tags:
- generated_from_trainer datasets:
- xsum metrics:
- rouge model-index:
- name: t5-small-finetuned-xsum-wei1
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: xsum
type: xsum
args: default
metrics:
- name: Rouge1 type: rouge value: 27.5875
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: xsum
type: xsum
args: default
metrics:
<!-- 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. -->
t5-small-finetuned-xsum-wei1
This model is a fine-tuned version of t5-small on the xsum dataset. It achieves the following results on the evaluation set:
- Loss: 2.5287
- Rouge1: 27.5875
- Rouge2: 7.4083
- Rougel: 21.5654
- Rougelsum: 21.5716
- Gen Len: 18.8205
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: 12
- eval_batch_size: 12
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 2.7677 | 1.0 | 3401 | 2.5441 | 27.4235 | 7.2208 | 21.3535 | 21.3636 | 18.8311 |
| 2.735 | 2.0 | 6802 | 2.5287 | 27.5875 | 7.4083 | 21.5654 | 21.5716 | 18.8205 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.9.0+cu111
- Datasets 1.14.0
- Tokenizers 0.10.3
