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metadata
library_name: transformers
license: apache-2.0
base_model: google/mt5-base
tags:
  - generated_from_trainer
metrics:
  - rouge
  - bleu
model-index:
  - name: mt5-base-qaqg-finetuned-SQuAD-id-sentence
    results: []

mt5-base-qaqg-finetuned-SQuAD-id-sentence

This model is a fine-tuned version of google/mt5-base on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 1.4176
  • Rouge: {'rouge1': 0.431906438503008, 'rouge2': 0.25499026452104945, 'rougeL': 0.39204274842839615, 'rougeLsum': 0.39456014504144676}
  • Rouge1: 0.4319
  • Rouge2: 0.2550
  • Rougel: 0.3920
  • Rougelsum: 0.3946
  • Bleu: 0.2255

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: 0.0001
  • 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: 5

Training results

Training Loss Epoch Step Validation Loss Rouge Rouge1 Rouge2 Rougel Rougelsum Bleu
1.8092 1.0 2000 1.5726 {'rouge1': 0.38857764947308354, 'rouge2': 0.2144816356866815, 'rougeL': 0.34718290508264066, 'rougeLsum': 0.3491704618702567} 0.3886 0.2145 0.3472 0.3492 0.2027
1.448 2.0 4000 1.4578 {'rouge1': 0.4201425066563658, 'rouge2': 0.24245589461633016, 'rougeL': 0.3801327577125928, 'rougeLsum': 0.38306624507182285} 0.4201 0.2425 0.3801 0.3831 0.2179
1.2703 3.0 6000 1.4241 {'rouge1': 0.42984982575843933, 'rouge2': 0.2542816232928319, 'rougeL': 0.38888435744081745, 'rougeLsum': 0.39130709798526525} 0.4298 0.2543 0.3889 0.3913 0.2251
1.2228 4.0 8000 1.4314 {'rouge1': 0.4293519247279466, 'rouge2': 0.2525711759038574, 'rougeL': 0.3885634471147471, 'rougeLsum': 0.3910623048069688} 0.4294 0.2526 0.3886 0.3911 0.2240
1.1391 5.0 10000 1.4176 {'rouge1': 0.431906438503008, 'rouge2': 0.25499026452104945, 'rougeL': 0.39204274842839615, 'rougeLsum': 0.39456014504144676} 0.4319 0.2550 0.3920 0.3946 0.2255

Framework versions

  • Transformers 4.44.2
  • Pytorch 2.4.0a0+f70bd71a48.nv24.06
  • Datasets 2.21.0
  • Tokenizers 0.19.1