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metadata
license: apache-2.0
base_model: t5-base
tags:
  - generated_from_trainer
metrics:
  - bleu
  - wer
model-index:
  - name: 10_randomization_model
    results: []

10_randomization_model

This model is a fine-tuned version of t5-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1399
  • Bleu: 0.0001
  • Wer: 0.9311
  • Rougel: 0.1663
  • Gen Len: 18.9987

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: 8
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 2
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Bleu Wer Rougel Gen Len
0.716 0.16 1000 0.2572 0.0001 0.932 0.1648 18.9987
0.2981 0.32 2000 0.2055 0.0001 0.9317 0.1655 18.9987
0.2596 0.48 3000 0.1836 0.0001 0.9315 0.1658 18.9987
0.2371 0.64 4000 0.1685 0.0001 0.9314 0.1659 18.9987
0.2266 0.8 5000 0.1616 0.0001 0.9313 0.1661 18.9987
0.2134 0.96 6000 0.1531 0.0001 0.9313 0.1662 18.9987
0.2035 1.12 7000 0.1505 0.0001 0.9312 0.1662 18.9987
0.1973 1.28 8000 0.1466 0.0001 0.9312 0.1663 18.9987
0.1942 1.44 9000 0.1430 0.0001 0.9312 0.1663 18.9987
0.1905 1.6 10000 0.1416 0.0001 0.9312 0.1663 18.9987
0.1892 1.76 11000 0.1402 0.0001 0.9312 0.1663 18.9987
0.1867 1.92 12000 0.1399 0.0001 0.9311 0.1663 18.9987

Framework versions

  • Transformers 4.37.1
  • Pytorch 2.3.0.dev20240122+cu121
  • Datasets 2.16.1
  • Tokenizers 0.15.1