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Training in progress epoch 29
15def42
metadata
license: apache-2.0
base_model: google/mt5-small
tags:
  - generated_from_keras_callback
model-index:
  - name: pakawadeep/mt5-small-finetuned-ctfl-augmented_2
    results: []

pakawadeep/mt5-small-finetuned-ctfl-augmented_2

This model is a fine-tuned version of google/mt5-small on an unknown dataset. It achieves the following results on the evaluation set:

  • Train Loss: 0.6759
  • Validation Loss: 0.9239
  • Train Rouge1: 7.9562
  • Train Rouge2: 1.3861
  • Train Rougel: 7.9562
  • Train Rougelsum: 7.9915
  • Train Gen Len: 11.9653
  • Epoch: 29

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:

  • optimizer: {'name': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
  • training_precision: float32

Training results

Train Loss Validation Loss Train Rouge1 Train Rouge2 Train Rougel Train Rougelsum Train Gen Len Epoch
8.2342 2.0102 1.5963 0.0 1.6101 1.6005 16.5050 0
3.7896 1.7810 4.8515 0.7426 4.8845 4.8680 11.8614 1
2.7018 1.7212 6.8812 1.4851 6.8812 6.8812 11.9554 2
2.1382 1.5885 7.8996 2.0792 7.9066 7.9066 11.9010 3
1.7718 1.4799 7.7086 2.0792 7.7086 7.7086 11.8911 4
1.5137 1.3902 7.7086 2.0792 7.7086 7.7086 11.9653 5
1.3341 1.3439 8.6987 2.0792 8.6987 8.6987 11.9307 6
1.2253 1.2605 8.6987 2.0792 8.6987 8.6987 11.9356 7
1.1425 1.2215 8.9816 2.3762 8.9816 8.9816 11.9356 8
1.0872 1.1772 8.9816 2.3762 8.9816 8.9816 11.9554 9
1.0400 1.1338 8.6987 1.8812 8.6987 8.7341 11.9604 10
0.9997 1.0986 8.6987 1.8812 8.6987 8.7341 11.9554 11
0.9732 1.0846 8.4512 1.3861 8.4158 8.4866 11.9653 12
0.9388 1.0718 8.4512 1.3861 8.4158 8.4866 11.9752 13
0.9140 1.0483 8.4512 1.3861 8.4158 8.4866 11.9505 14
0.8902 1.0285 8.4512 1.3861 8.4158 8.4866 11.9554 15
0.8704 1.0147 8.4512 1.3861 8.4158 8.4866 11.9505 16
0.8490 1.0094 8.4512 1.3861 8.4158 8.4866 11.9505 17
0.8338 0.9880 7.9562 1.3861 7.9562 7.9915 11.9406 18
0.8139 0.9921 7.9562 1.3861 7.9562 7.9915 11.9455 19
0.7992 0.9765 7.9562 1.3861 7.9562 7.9915 11.9604 20
0.7806 0.9704 7.9562 1.3861 7.9562 7.9915 11.9604 21
0.7651 0.9523 7.9562 1.3861 7.9562 7.9915 11.9554 22
0.7560 0.9615 7.9562 1.3861 7.9562 7.9915 11.9653 23
0.7370 0.9489 7.9562 1.3861 7.9562 7.9915 11.9752 24
0.7263 0.9350 7.9562 1.3861 7.9562 7.9915 11.9604 25
0.7111 0.9425 7.9562 1.3861 7.9562 7.9915 11.9802 26
0.7005 0.9348 7.9562 1.3861 7.9562 7.9915 11.9752 27
0.6912 0.9213 7.9562 1.3861 7.9562 7.9915 11.9752 28
0.6759 0.9239 7.9562 1.3861 7.9562 7.9915 11.9653 29

Framework versions

  • Transformers 4.41.2
  • TensorFlow 2.15.0
  • Datasets 2.20.0
  • Tokenizers 0.19.1