metadata
license: apache-2.0
base_model: google/mt5-small
tags:
- generated_from_trainer
datasets:
- wmt16
metrics:
- rouge
- sacrebleu
model-index:
- name: mt5_small_wmt16_de_en
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: wmt16
type: wmt16
config: de-en
split: validation
args: de-en
metrics:
- name: Rouge1
type: rouge
value: 0.3666
- name: Sacrebleu
type: sacrebleu
value: 6.4622
mt5_small_wmt16_de_en
This model is a fine-tuned version of google/mt5-small on the wmt16 dataset. It achieves the following results on the evaluation set:
- Loss: 2.4612
- Rouge1: 0.3666
- Rouge2: 0.147
- Rougel: 0.3362
- Sacrebleu: 6.4622
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Sacrebleu |
|---|---|---|---|---|---|---|---|
| 3.3059 | 1.6 | 500 | 2.5597 | 0.3398 | 0.1261 | 0.3068 | 5.5524 |
| 2.4093 | 3.2 | 1000 | 2.4996 | 0.3609 | 0.144 | 0.3304 | 6.2002 |
| 2.2322 | 4.8 | 1500 | 2.4612 | 0.3666 | 0.147 | 0.3362 | 6.4622 |
Framework versions
- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3