Nahuatl_Espanol_vn / README.md
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metadata
tags:
  - generated_from_trainer
metrics:
  - bleu
model-index:
  - name: Nahuatl_Espanol_vn
    results: []

Nahuatl_Espanol_vn

This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 1.1464
  • Bleu: 15.4218
  • Gen Len: 45.5239

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: 0.0003
  • 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
  • num_epochs: 3

Training results

Training Loss Epoch Step Validation Loss Bleu Gen Len
No log 0.1064 100 1.1525 14.738 46.3599
No log 0.2128 200 1.1682 14.2823 45.9297
No log 0.3191 300 1.1739 14.2118 46.4243
No log 0.4255 400 1.1799 14.3198 45.9266
1.3984 0.5319 500 1.1771 14.0972 46.2179
1.3984 0.6383 600 1.1752 14.4083 45.8709
1.3984 0.7447 700 1.1756 14.1914 46.0949
1.3984 0.8511 800 1.1761 14.4131 46.0528
1.3984 0.9574 900 1.1727 14.1957 46.4856
1.3826 1.0638 1000 1.1768 14.7451 45.7873
1.3826 1.1702 1100 1.1727 14.6016 45.8654
1.3826 1.2766 1200 1.1726 14.6549 45.6857
1.3826 1.3830 1300 1.1693 14.586 45.6052
1.3826 1.4894 1400 1.1704 14.6483 45.6039
1.2932 1.5957 1500 1.1638 14.921 45.5508
1.2932 1.7021 1600 1.1649 14.7977 45.3693
1.2932 1.8085 1700 1.1580 14.9676 45.7072
1.2932 1.9149 1800 1.1567 14.794 45.5877
1.2932 2.0213 1900 1.1607 15.3066 45.677
1.2612 2.1277 2000 1.1569 15.1152 45.4122
1.2612 2.2340 2100 1.1553 15.2526 45.4026
1.2612 2.3404 2200 1.1521 15.2022 45.3518
1.2612 2.4468 2300 1.1505 15.3072 45.5873
1.2612 2.5532 2400 1.1500 15.417 45.5906
1.2095 2.6596 2500 1.1507 15.394 45.4383
1.2095 2.7660 2600 1.1501 15.4171 45.4846
1.2095 2.8723 2700 1.1472 15.4497 45.5049
1.2095 2.9787 2800 1.1464 15.4218 45.5239

Framework versions

  • Transformers 4.41.0
  • Pytorch 2.3.0+cu121
  • Datasets 2.19.1
  • Tokenizers 0.19.1