---
tags:
- generated_from_trainer
datasets:
- opus100
metrics:
- bleu
model-index:
- name: opus-mt-en-id-opus100
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: opus100
      type: opus100
      config: en-id
      split: validation
      args: en-id
    metrics:
    - name: Bleu
      type: bleu
      value: 27.5354
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# opus-mt-en-id-opus100

This model was trained from scratch on the opus100 dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3682
- Bleu: 27.5354

## 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: 0.0001
- 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
- lr_scheduler_warmup_steps: 4000
- num_epochs: 25

### Training results

| Training Loss | Epoch | Step   | Validation Loss | Bleu    |
|:-------------:|:-----:|:------:|:---------------:|:-------:|
| 1.6086        | 1.0   | 31250  | 1.7099          | 29.4293 |
| 1.5762        | 2.0   | 62500  | 1.7410          | 28.948  |
| 1.5027        | 3.0   | 93750  | 1.7678          | 28.6931 |
| 1.4377        | 4.0   | 125000 | 1.7798          | 28.9463 |
| 1.3763        | 5.0   | 156250 | 1.8019          | 28.4966 |
| 1.3198        | 6.0   | 187500 | 1.8202          | 29.6279 |
| 1.2648        | 7.0   | 218750 | 1.8312          | 29.8151 |
| 1.2115        | 8.0   | 250000 | 1.8490          | 29.3032 |
| 1.1584        | 9.0   | 281250 | 1.8729          | 28.7282 |
| 1.1067        | 10.0  | 312500 | 1.8971          | 29.4797 |
| 1.0555        | 11.0  | 343750 | 1.9405          | 29.3416 |
| 1.0052        | 12.0  | 375000 | 1.9554          | 29.0168 |
| 0.956         | 13.0  | 406250 | 2.0001          | 28.2454 |
| 0.9069        | 14.0  | 437500 | 2.0282          | 28.6705 |
| 0.8589        | 15.0  | 468750 | 2.0591          | 28.1988 |
| 0.8115        | 16.0  | 500000 | 2.0944          | 28.2227 |
| 0.765         | 17.0  | 531250 | 2.1294          | 28.4351 |
| 0.7203        | 18.0  | 562500 | 2.1680          | 27.9764 |
| 0.6769        | 19.0  | 593750 | 2.2013          | 28.2986 |
| 0.6349        | 20.0  | 625000 | 2.2339          | 27.165  |
| 0.5957        | 21.0  | 656250 | 2.2795          | 27.5845 |
| 0.5589        | 22.0  | 687500 | 2.3037          | 27.7201 |
| 0.5246        | 23.0  | 718750 | 2.3311          | 27.3305 |
| 0.4944        | 24.0  | 750000 | 2.3487          | 27.3965 |
| 0.469         | 25.0  | 781250 | 2.3682          | 27.5354 |


### Framework versions

- Transformers 4.26.1
- Pytorch 2.0.0
- Datasets 2.10.1
- Tokenizers 0.11.0