---
tags:
- generated_from_trainer
datasets:
- opus100
metrics:
- bleu
model-index:
- name: opus-mt-id-en-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: 32.455
---

<!-- 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-id-en-opus100

This model was trained from scratch on the opus100 dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1008
- Bleu: 32.455

## 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    |
|:-------------:|:-----:|:------:|:---------------:|:-------:|
| 1.4869        | 1.0   | 31250  | 1.6303          | 32.7596 |
| 1.433         | 2.0   | 62500  | 1.6474          | 33.1603 |
| 1.3626        | 3.0   | 93750  | 1.6541          | 32.6599 |
| 1.3025        | 4.0   | 125000 | 1.6538          | 32.961  |
| 1.2485        | 5.0   | 156250 | 1.6630          | 33.1362 |
| 1.198         | 6.0   | 187500 | 1.6794          | 32.0117 |
| 1.1492        | 7.0   | 218750 | 1.6910          | 33.2442 |
| 1.102         | 8.0   | 250000 | 1.6874          | 32.7068 |
| 1.0559        | 9.0   | 281250 | 1.6944          | 32.8825 |
| 1.0106        | 10.0  | 312500 | 1.7288          | 33.2979 |
| 0.9662        | 11.0  | 343750 | 1.7402          | 33.255  |
| 0.9219        | 12.0  | 375000 | 1.7589          | 32.901  |
| 0.8783        | 13.0  | 406250 | 1.7893          | 32.6629 |
| 0.8352        | 14.0  | 437500 | 1.8074          | 32.6507 |
| 0.7932        | 15.0  | 468750 | 1.8359          | 33.0076 |
| 0.7516        | 16.0  | 500000 | 1.8694          | 32.9601 |
| 0.7112        | 17.0  | 531250 | 1.8887          | 32.5161 |
| 0.6711        | 18.0  | 562500 | 1.9194          | 32.5722 |
| 0.6326        | 19.0  | 593750 | 1.9512          | 32.553  |
| 0.5955        | 20.0  | 625000 | 1.9791          | 32.0152 |
| 0.5603        | 21.0  | 656250 | 2.0104          | 32.2671 |
| 0.5266        | 22.0  | 687500 | 2.0388          | 32.1775 |
| 0.4956        | 23.0  | 718750 | 2.0663          | 32.123  |
| 0.4681        | 24.0  | 750000 | 2.0849          | 32.1197 |
| 0.4445        | 25.0  | 781250 | 2.1008          | 32.455  |


### Framework versions

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