metadata
license: apache-2.0
tags:
- summarization
- generated_from_trainer
datasets:
- xlsum
metrics:
- rouge
model-index:
- name: mt5-small-finetuned-mt5-en
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: xlsum
type: xlsum
args: english
metrics:
- name: Rouge1
type: rouge
value: 23.8952
mt5-small-finetuned-mt5-en
This model is a fine-tuned version of google/mt5-small on the xlsum dataset. It achieves the following results on the evaluation set:
- Loss: 2.8345
- Rouge1: 23.8952
- Rouge2: 5.8792
- Rougel: 18.6495
- Rougelsum: 18.7057
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: 0.0005
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 10
- total_train_batch_size: 40
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 224 | 3.0150 | 24.4639 | 5.3016 | 18.3987 | 18.4963 |
| No log | 2.0 | 448 | 2.8738 | 24.5075 | 5.842 | 18.8133 | 18.9072 |
| No log | 3.0 | 672 | 2.8345 | 23.8952 | 5.8792 | 18.6495 | 18.7057 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.10.0+cu111
- Datasets 2.0.0
- Tokenizers 0.11.6