Jérôme Bau
update model card README.md
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metadata
license: apache-2.0
base_model: t5-small
tags:
  - generated_from_trainer
metrics:
  - rouge
model-index:
  - name: t5-small-finetuned-coding_instructions_2023_08_18__08_41
    results: []

t5-small-finetuned-coding_instructions_2023_08_18__08_41

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

  • Loss: 1.9209
  • Rouge1: 13.9516
  • Rouge2: 6.1527
  • Rougel: 13.1037
  • Rougelsum: 13.1244
  • Gen Len: 18.3077

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: 16
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10

Training results

Training Loss Epoch Step Validation Loss Rouge1 Rouge2 Rougel Rougelsum Gen Len
No log 1.0 5 2.6656 8.6104 3.1562 8.1185 8.1422 19.0
No log 2.0 10 2.5149 9.7852 3.836 9.3185 9.3322 19.0
No log 3.0 15 2.3683 13.1134 5.2015 12.1364 12.2677 19.0
No log 4.0 20 2.2032 13.4182 5.1369 12.5255 12.6118 19.0
No log 5.0 25 2.0986 13.6902 5.3556 12.7848 12.898 19.0
No log 6.0 30 2.0232 12.7675 4.8786 11.9464 11.9539 18.3846
No log 7.0 35 1.9857 13.9444 6.1527 13.0926 13.1171 18.5385
No log 8.0 40 1.9526 13.9516 6.1527 13.1037 13.1244 18.5385
No log 9.0 45 1.9303 13.9516 6.1527 13.1037 13.1244 18.3077
No log 10.0 50 1.9209 13.9516 6.1527 13.1037 13.1244 18.3077

Framework versions

  • Transformers 4.31.0
  • Pytorch 2.0.1+cu118
  • Datasets 2.14.4
  • Tokenizers 0.13.3