readme: ---
  license: apache-2.0
  tags:
  - generated_from_trainer
  metrics:
  - bleu
  model-index:
  - name: nmt-mpst-id-en-lr_0.001-ep_30-seq_128_bs-16
    results: []
  ---
  
  <!-- 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. -->
  
  # nmt-mpst-id-en-lr_0.001-ep_30-seq_128_bs-16
  
  This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.3591
  - Bleu: 0.2073
  - Meteor: 0.3779
  
  ## 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: 0.001
  - 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: 30
  
  ### Training results
  
  | Training Loss | Epoch | Step  | Validation Loss | Bleu   | Meteor |
  |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
  | No log        | 1.0   | 404   | 2.0642          | 0.1068 | 0.2561 |
  | 2.5607        | 2.0   | 808   | 1.7482          | 0.1392 | 0.299  |
  | 1.7768        | 3.0   | 1212  | 1.6392          | 0.1614 | 0.325  |
  | 1.4132        | 4.0   | 1616  | 1.6131          | 0.1728 | 0.3418 |
  | 1.205         | 5.0   | 2020  | 1.5724          | 0.1854 | 0.3543 |
  | 1.205         | 6.0   | 2424  | 1.5988          | 0.1897 | 0.3592 |
  | 1.0069        | 7.0   | 2828  | 1.5839          | 0.1922 | 0.3618 |
  | 0.8711        | 8.0   | 3232  | 1.6187          | 0.196  | 0.3678 |
  | 0.7759        | 9.0   | 3636  | 1.6453          | 0.1968 | 0.3672 |
  | 0.6838        | 10.0  | 4040  | 1.6837          | 0.1981 | 0.3685 |
  | 0.6838        | 11.0  | 4444  | 1.7401          | 0.1976 | 0.3698 |
  | 0.5903        | 12.0  | 4848  | 1.7686          | 0.2016 | 0.3712 |
  | 0.5207        | 13.0  | 5252  | 1.8075          | 0.2026 | 0.3733 |
  | 0.4712        | 14.0  | 5656  | 1.8665          | 0.2028 | 0.3743 |
  | 0.4154        | 15.0  | 6060  | 1.9114          | 0.204  | 0.3746 |
  | 0.4154        | 16.0  | 6464  | 1.9556          | 0.2036 | 0.376  |
  | 0.3726        | 17.0  | 6868  | 1.9961          | 0.2011 | 0.374  |
  | 0.326         | 18.0  | 7272  | 2.0437          | 0.2027 | 0.3739 |
  | 0.2936        | 19.0  | 7676  | 2.0946          | 0.2038 | 0.3754 |
  | 0.2671        | 20.0  | 8080  | 2.1319          | 0.2041 | 0.374  |
  | 0.2671        | 21.0  | 8484  | 2.1717          | 0.2044 | 0.3756 |
  | 0.2407        | 22.0  | 8888  | 2.2025          | 0.2045 | 0.3756 |
  | 0.2143        | 23.0  | 9292  | 2.2375          | 0.2031 | 0.3734 |
  | 0.1974        | 24.0  | 9696  | 2.2544          | 0.2057 | 0.3765 |
  | 0.182         | 25.0  | 10100 | 2.2875          | 0.2057 | 0.3767 |
  | 0.1686        | 26.0  | 10504 | 2.3153          | 0.2048 | 0.3762 |
  | 0.1686        | 27.0  | 10908 | 2.3395          | 0.2063 | 0.3786 |
  | 0.1548        | 28.0  | 11312 | 2.3493          | 0.2071 | 0.3783 |
  | 0.145         | 29.0  | 11716 | 2.3569          | 0.2072 | 0.3781 |
  | 0.1412        | 30.0  | 12120 | 2.3591          | 0.2073 | 0.3779 |
  
  
  ### Framework versions
  
  - Transformers 4.24.0
  - Pytorch 1.12.1+cu113
  - Datasets 2.7.0
  - Tokenizers 0.13.2
  