metadata
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- id_panl_bppt
metrics:
- bleu
model-index:
- name: opus-mt-id-en-finetuned-id-to-en
results:
- task:
name: Sequence-to-sequence Language Modeling
type: text2text-generation
dataset:
name: id_panl_bppt
type: id_panl_bppt
config: id_panl_bppt
split: train
args: id_panl_bppt
metrics:
- name: Bleu
type: bleu
value: 30.557
opus-mt-id-en-finetuned-id-to-en
This model is a fine-tuned version of Helsinki-NLP/opus-mt-id-en on the id_panl_bppt dataset. It achieves the following results on the evaluation set:
- Loss: 1.6469
- Bleu: 30.557
- Gen Len: 29.8247
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-06
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Bleu | Gen Len |
|---|---|---|---|---|---|
| 2.5737 | 1.0 | 751 | 2.2222 | 24.4223 | 30.3344 |
| 2.3756 | 2.0 | 1502 | 2.1264 | 25.419 | 30.3147 |
| 2.3146 | 3.0 | 2253 | 2.0588 | 26.0995 | 30.1959 |
| 2.2411 | 4.0 | 3004 | 2.0072 | 26.5944 | 30.0763 |
| 2.1927 | 5.0 | 3755 | 1.9657 | 27.0422 | 30.0773 |
| 2.1554 | 6.0 | 4506 | 1.9284 | 27.4151 | 30.0715 |
| 2.1105 | 7.0 | 5257 | 1.8980 | 27.6645 | 29.9426 |
| 2.0841 | 8.0 | 6008 | 1.8680 | 28.023 | 29.9797 |
| 2.0491 | 9.0 | 6759 | 1.8438 | 28.2456 | 29.9342 |
| 2.0265 | 10.0 | 7510 | 1.8218 | 28.5378 | 29.8968 |
| 2.0065 | 11.0 | 8261 | 1.8012 | 28.7599 | 29.8907 |
| 1.9764 | 12.0 | 9012 | 1.7835 | 28.9369 | 29.8796 |
| 1.969 | 13.0 | 9763 | 1.7663 | 29.1565 | 29.8671 |
| 1.9474 | 14.0 | 10514 | 1.7506 | 29.3313 | 29.893 |
| 1.9397 | 15.0 | 11265 | 1.7378 | 29.4567 | 29.8512 |
| 1.9217 | 16.0 | 12016 | 1.7239 | 29.6245 | 29.8361 |
| 1.9174 | 17.0 | 12767 | 1.7127 | 29.7464 | 29.8398 |
| 1.9021 | 18.0 | 13518 | 1.7030 | 29.9035 | 29.8621 |
| 1.89 | 19.0 | 14269 | 1.6934 | 29.9669 | 29.8225 |
| 1.878 | 20.0 | 15020 | 1.6847 | 30.0961 | 29.8398 |
| 1.8671 | 21.0 | 15771 | 1.6774 | 30.1878 | 29.839 |
| 1.8634 | 22.0 | 16522 | 1.6717 | 30.2341 | 29.8134 |
| 1.8536 | 23.0 | 17273 | 1.6653 | 30.3356 | 29.816 |
| 1.8533 | 24.0 | 18024 | 1.6602 | 30.3548 | 29.8251 |
| 1.8476 | 25.0 | 18775 | 1.6560 | 30.4323 | 29.8315 |
| 1.8362 | 26.0 | 19526 | 1.6528 | 30.4682 | 29.8277 |
| 1.8463 | 27.0 | 20277 | 1.6501 | 30.5002 | 29.8236 |
| 1.8369 | 28.0 | 21028 | 1.6484 | 30.5236 | 29.8257 |
| 1.8313 | 29.0 | 21779 | 1.6472 | 30.55 | 29.8259 |
| 1.8332 | 30.0 | 22530 | 1.6469 | 30.557 | 29.8247 |
Framework versions
- Transformers 4.21.1
- Pytorch 1.12.0
- Datasets 2.4.0
- Tokenizers 0.12.1