metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- billsum
metrics:
- rouge
base_model: t5-small
model-index:
- name: my_awesome_billsum_model
results:
- task:
type: text2text-generation
name: Sequence-to-sequence Language Modeling
dataset:
name: billsum
type: billsum
config: default
split: ca_test
args: default
metrics:
- type: rouge
value: 0.1394
name: Rouge1
my_awesome_billsum_model
This model is a fine-tuned version of t5-small on the billsum dataset. It achieves the following results on the evaluation set:
- Loss: 2.5824
- Rouge1: 0.1394
- Rouge2: 0.0502
- Rougel: 0.1134
- Rougelsum: 0.1133
- 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: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- 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 |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 55 | 2.9056 | 0.1255 | 0.0372 | 0.1049 | 0.1049 | 19.0 |
| No log | 2.0 | 110 | 2.6665 | 0.1345 | 0.0456 | 0.1098 | 0.11 | 19.0 |
| No log | 3.0 | 165 | 2.6010 | 0.1378 | 0.0485 | 0.1122 | 0.1123 | 19.0 |
| No log | 4.0 | 220 | 2.5824 | 0.1394 | 0.0502 | 0.1134 | 0.1133 | 19.0 |
Framework versions
- Transformers 4.29.2
- Pytorch 1.13.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3