---
tags:
- generated_from_trainer
datasets:
- data
metrics:
- bleu
model-index:
- name: mbart-en-id-smaller-indo-amr-generation-translated-nafkhan
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: data
      type: data
      config: default
      split: validation
      args: default
    metrics:
    - name: Bleu
      type: bleu
      value: 50.4231
---

<!-- 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. -->

# mbart-en-id-smaller-indo-amr-generation-translated-nafkhan

This model was trained from scratch on the data dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9816
- Bleu: 50.4231
- Gen Len: 8.2667

## 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: 1e-06
- train_batch_size: 5
- eval_batch_size: 5
- seed: 42
- gradient_accumulation_steps: 5
- total_train_batch_size: 25
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: polynomial
- lr_scheduler_warmup_steps: 200
- num_epochs: 640.0
- label_smoothing_factor: 0.1

### Training results

| Training Loss | Epoch    | Step  | Validation Loss | Bleu    | Gen Len |
|:-------------:|:--------:|:-----:|:---------------:|:-------:|:-------:|
| 1.5364        | 39.7351  | 3600  | 2.0474          | 41.1359 | 9.5667  |
| 1.4794        | 79.4702  | 7200  | 2.0256          | 44.4125 | 9.0667  |
| 1.3621        | 119.2053 | 10800 | 2.0037          | 49.121  | 8.8     |
| 1.3278        | 158.9404 | 14400 | 1.9857          | 52.1498 | 8.5     |
| 1.2906        | 198.6755 | 18000 | 2.0048          | 48.3044 | 8.5333  |
| 1.2272        | 238.4106 | 21600 | 2.0017          | 47.3367 | 8.6     |
| 1.2339        | 278.1457 | 25200 | 1.9705          | 46.5655 | 8.5667  |
| 1.194         | 317.8808 | 28800 | 1.9818          | 51.4066 | 8.5     |
| 1.1416        | 357.6159 | 32400 | 1.9699          | 45.7022 | 8.4333  |
| 1.1437        | 397.3510 | 36000 | 1.9692          | 46.8726 | 8.2     |
| 1.156         | 437.0861 | 39600 | 1.9549          | 48.7386 | 8.4333  |
| 1.1355        | 476.8212 | 43200 | 1.9726          | 48.3929 | 8.5667  |
| 1.1246        | 516.5563 | 46800 | 1.9701          | 47.8897 | 8.4667  |
| 1.1132        | 556.2914 | 50400 | 1.9736          | 48.9071 | 8.3667  |
| 1.0843        | 596.0265 | 54000 | 1.9765          | 49.9897 | 8.4333  |
| 1.1211        | 635.7616 | 57600 | 1.9816          | 50.4231 | 8.2667  |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0
- Datasets 2.20.0
- Tokenizers 0.19.1