metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- wmt16
metrics:
- bleu
model-index:
- name: opus-mt-de-en-finetuned-de-to-en-second
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: wmt16
type: wmt16
args: de-en
metrics:
- name: Bleu
type: bleu
value: 38.959
opus-mt-de-en-finetuned-de-to-en-second
This model is a fine-tuned version of Helsinki-NLP/opus-mt-de-en on the wmt16 dataset. It achieves the following results on the evaluation set:
- Loss: 1.1719
- Bleu: 38.959
- Gen Len: 25.2812
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
---|---|---|---|---|---|
No log | 1.0 | 157 | 1.1492 | 39.2552 | 25.2268 |
No log | 2.0 | 314 | 1.1601 | 38.8343 | 25.2288 |
No log | 3.0 | 471 | 1.1651 | 39.0092 | 25.254 |
1.8512 | 4.0 | 628 | 1.1704 | 38.9281 | 25.2756 |
1.8512 | 5.0 | 785 | 1.1719 | 38.959 | 25.2812 |
Framework versions
- Transformers 4.12.5
- Pytorch 1.10.0+cu111
- Datasets 1.16.1
- Tokenizers 0.10.3