readme: ---
  license: apache-2.0
  tags:
  - translation
  - generated_from_trainer
  metrics:
  - bleu
  model-index:
  - name: En-Nso_update
    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. -->
  
  # En-Nso_update
  
  This model is a fine-tuned version of [Helsinki-NLP/opus-mt-en-nso](https://huggingface.co/Helsinki-NLP/opus-mt-en-nso) on the None dataset.
  It achieves the following results on the evaluation set:
  - Loss: 2.8782
  - Bleu: 31.2967
  
  ## 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-05
  - train_batch_size: 16
  - eval_batch_size: 32
  - seed: 42
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  - lr_scheduler_type: linear
  - num_epochs: 100
  
  ### Training results
  
  | Training Loss | Epoch | Step | Validation Loss | Bleu    |
  |:-------------:|:-----:|:----:|:---------------:|:-------:|
  | No log        | 1.0   | 4    | 7.2950          | 0.0088  |
  | No log        | 2.0   | 8    | 5.9614          | 0.6848  |
  | No log        | 3.0   | 12   | 5.0695          | 4.9050  |
  | No log        | 4.0   | 16   | 4.5523          | 9.1757  |
  | No log        | 5.0   | 20   | 4.2355          | 10.4744 |
  | No log        | 6.0   | 24   | 4.0106          | 14.6163 |
  | No log        | 7.0   | 28   | 3.8427          | 15.8379 |
  | No log        | 8.0   | 32   | 3.7264          | 15.6158 |
  | No log        | 9.0   | 36   | 3.6338          | 16.3562 |
  | No log        | 10.0  | 40   | 3.5555          | 21.1011 |
  | No log        | 11.0  | 44   | 3.4839          | 21.5754 |
  | No log        | 12.0  | 48   | 3.4180          | 22.7155 |
  | No log        | 13.0  | 52   | 3.3620          | 23.1592 |
  | No log        | 14.0  | 56   | 3.3115          | 24.3886 |
  | No log        | 15.0  | 60   | 3.2676          | 24.1278 |
  | No log        | 16.0  | 64   | 3.2285          | 24.2245 |
  | No log        | 17.0  | 68   | 3.1974          | 23.9716 |
  | No log        | 18.0  | 72   | 3.1695          | 24.2395 |
  | No log        | 19.0  | 76   | 3.1441          | 23.3442 |
  | No log        | 20.0  | 80   | 3.1235          | 21.3332 |
  | No log        | 21.0  | 84   | 3.1029          | 21.8410 |
  | No log        | 22.0  | 88   | 3.0849          | 22.4065 |
  | No log        | 23.0  | 92   | 3.0666          | 22.3016 |
  | No log        | 24.0  | 96   | 3.0534          | 22.9616 |
  | No log        | 25.0  | 100  | 3.0423          | 23.3971 |
  | No log        | 26.0  | 104  | 3.0306          | 23.5443 |
  | No log        | 27.0  | 108  | 3.0183          | 23.3348 |
  | No log        | 28.0  | 112  | 3.0051          | 23.4077 |
  | No log        | 29.0  | 116  | 2.9947          | 24.1791 |
  | No log        | 30.0  | 120  | 2.9855          | 24.1265 |
  | No log        | 31.0  | 124  | 2.9777          | 23.9860 |
  | No log        | 32.0  | 128  | 2.9691          | 24.7301 |
  | No log        | 33.0  | 132  | 2.9597          | 25.1896 |
  | No log        | 34.0  | 136  | 2.9521          | 24.5893 |
  | No log        | 35.0  | 140  | 2.9457          | 24.5229 |
  | No log        | 36.0  | 144  | 2.9409          | 24.6232 |
  | No log        | 37.0  | 148  | 2.9354          | 24.2830 |
  | No log        | 38.0  | 152  | 2.9322          | 26.1404 |
  | No log        | 39.0  | 156  | 2.9306          | 25.9425 |
  | No log        | 40.0  | 160  | 2.9288          | 30.5432 |
  | No log        | 41.0  | 164  | 2.9261          | 29.4635 |
  | No log        | 42.0  | 168  | 2.9215          | 28.4787 |
  | No log        | 43.0  | 172  | 2.9182          | 28.9082 |
  | No log        | 44.0  | 176  | 2.9151          | 29.3171 |
  | No log        | 45.0  | 180  | 2.9132          | 28.3602 |
  | No log        | 46.0  | 184  | 2.9126          | 28.9583 |
  | No log        | 47.0  | 188  | 2.9104          | 26.0269 |
  | No log        | 48.0  | 192  | 2.9086          | 29.6904 |
  | No log        | 49.0  | 196  | 2.9052          | 29.2881 |
  | No log        | 50.0  | 200  | 2.9020          | 29.6063 |
  | No log        | 51.0  | 204  | 2.8994          | 29.5224 |
  | No log        | 52.0  | 208  | 2.8960          | 29.3913 |
  | No log        | 53.0  | 212  | 2.8930          | 30.5451 |
  | No log        | 54.0  | 216  | 2.8889          | 32.1862 |
  | No log        | 55.0  | 220  | 2.8869          | 31.9423 |
  | No log        | 56.0  | 224  | 2.8859          | 30.7244 |
  | No log        | 57.0  | 228  | 2.8846          | 30.8172 |
  | No log        | 58.0  | 232  | 2.8837          | 30.5376 |
  | No log        | 59.0  | 236  | 2.8826          | 31.1454 |
  | No log        | 60.0  | 240  | 2.8813          | 30.9049 |
  | No log        | 61.0  | 244  | 2.8802          | 30.6363 |
  | No log        | 62.0  | 248  | 2.8802          | 31.3739 |
  | No log        | 63.0  | 252  | 2.8799    