metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- multi_news
metrics:
- rouge
model-index:
- name: my_awesome_billsum_model
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: multi_news
type: multi_news
config: default
split: test
args: default
metrics:
- name: Rouge1
type: rouge
value: 0.1003
my_awesome_billsum_model
This model is a fine-tuned version of t5-small on the multi_news dataset. It achieves the following results on the evaluation set:
- Loss: 2.6768
- Rouge1: 0.1003
- Rouge2: 0.0337
- Rougel: 0.0777
- Rougelsum: 0.0777
- Gen Len: 19.0
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: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 3.0003 | 1.0 | 22486 | 2.7383 | 0.0993 | 0.0332 | 0.077 | 0.077 | 19.0 |
| 2.9276 | 2.0 | 44972 | 2.6999 | 0.1001 | 0.0332 | 0.0774 | 0.0774 | 19.0 |
| 2.9036 | 3.0 | 67458 | 2.6795 | 0.1004 | 0.0338 | 0.0778 | 0.0778 | 19.0 |
| 2.9043 | 4.0 | 89944 | 2.6768 | 0.1003 | 0.0337 | 0.0777 | 0.0777 | 19.0 |
Framework versions
- Transformers 4.27.1
- Pytorch 1.13.1+cu116
- Datasets 2.10.1
- Tokenizers 0.13.2