metadata
license: apache-2.0
tags:
- summarization_v1_m5
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: mt5-small-finetune-sumsum
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: samsum
type: samsum
args: samsum
metrics:
- name: Rouge1
type: rouge
value: 20.9651
mt5-small-finetune-sumsum
This model is a fine-tuned version of google/mt5-small on the samsum dataset. It achieves the following results on the evaluation set:
- Loss: 3.3263
- Rouge1: 20.9651
- Rouge2: 7.1527
- Rougel: 18.4396
- Rougelsum: 19.5209
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| 12.2648 | 1.0 | 125 | 4.3790 | 9.8078 | 1.7255 | 9.0852 | 9.4233 |
| 6.0853 | 2.0 | 250 | 3.4753 | 20.7185 | 6.502 | 18.079 | 19.2584 |
| 4.9838 | 3.0 | 375 | 3.3263 | 20.9651 | 7.1527 | 18.4396 | 19.5209 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.13.0
- Datasets 2.6.1
- Tokenizers 0.11.0