metadata
license: apache-2.0
tags:
- summarization
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: t5-v1_1-small-finetuned-samsum
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: samsum
type: samsum
config: samsum
split: train
args: samsum
metrics:
- name: Rouge1
type: rouge
value: 0.40608242084369006
t5-v1_1-small-finetuned-samsum
This model is a fine-tuned version of google/t5-v1_1-small on the samsum dataset. It achieves the following results on the evaluation set:
- Loss: 2.0053
- Rouge1: 0.4061
- Rouge2: 0.1804
- Rougel: 0.3478
- Rougelsum: 0.3774
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: 5.6e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 3.9788 | 1.0 | 1842 | 2.2499 | 0.3743 | 0.1569 | 0.3191 | 0.3486 |
| 2.9091 | 2.0 | 3684 | 2.1052 | 0.3875 | 0.1680 | 0.3329 | 0.3607 |
| 2.6807 | 3.0 | 5526 | 2.0270 | 0.4009 | 0.1778 | 0.3439 | 0.3734 |
| 2.5917 | 4.0 | 7368 | 2.0053 | 0.4061 | 0.1804 | 0.3478 | 0.3774 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2