metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- cnn_dailymail
metrics:
- rouge
model-index:
- name: t5-small-finetuned-cnn-2
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: cnn_dailymail
type: cnn_dailymail
args: 3.0.0
metrics:
- name: Rouge1
type: rouge
value: 24.5085
t5-small-finetuned-cnn-2
This model is a fine-tuned version of t5-small on the cnn_dailymail dataset. It achieves the following results on the evaluation set:
- Loss: 1.6620
- Rouge1: 24.5085
- Rouge2: 11.7925
- Rougel: 20.2631
- Rougelsum: 23.1253
- Gen Len: 18.9996
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: 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: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|---|---|---|---|---|---|---|---|---|
| 1.8435 | 1.0 | 35890 | 1.6753 | 24.5387 | 11.7851 | 20.2792 | 23.1595 | 18.999 |
| 1.8143 | 2.0 | 71780 | 1.6660 | 24.5268 | 11.7976 | 20.2699 | 23.1384 | 18.9996 |
| 1.816 | 3.0 | 107670 | 1.6620 | 24.5085 | 11.7925 | 20.2631 | 23.1253 | 18.9996 |
Framework versions
- Transformers 4.16.2
- Pytorch 1.10.2+cu102
- Datasets 1.18.3
- Tokenizers 0.11.0