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Training in progress epoch 29
a1391fc
metadata
license: apache-2.0
base_model: google/mt5-base
tags:
  - generated_from_keras_callback
model-index:
  - name: pakawadeep/mt5-base-finetuned-ctfl-augmented_2
    results: []

pakawadeep/mt5-base-finetuned-ctfl-augmented_2

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

  • Train Loss: 0.3928
  • Validation Loss: 0.7920
  • Train Rouge1: 8.6516
  • Train Rouge2: 0.8911
  • Train Rougel: 8.6634
  • Train Rougelsum: 8.8579
  • Train Gen Len: 11.9109
  • 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
6.2987 3.0653 5.1273 0.9901 5.0743 5.2334 7.9208 0
2.9686 2.1339 6.0644 1.3201 6.1056 6.1056 9.7277 1
1.9868 1.6122 6.4356 1.6832 6.5535 6.5064 11.2970 2
1.4819 1.2447 8.2744 2.1782 8.3663 8.4017 11.7921 3
1.5597 1.4425 7.9208 2.3762 7.9915 8.0387 11.7376 4
1.2413 1.2182 8.8048 2.1782 8.8826 8.9109 11.8713 5
1.2091 1.2376 7.7793 1.3861 7.9208 7.9915 11.8861 6
1.0808 1.1154 8.2744 1.3861 8.4512 8.5219 11.9455 7
0.9719 1.0578 7.9915 1.1881 8.1683 8.2037 11.9604 8
1.0497 1.0547 8.4394 1.3861 8.4925 8.6103 11.9158 9
0.9426 1.0468 8.2744 1.3861 8.4512 8.5219 11.9455 10
0.8904 0.9902 8.1565 0.8911 8.2567 8.3687 11.9257 11
0.8371 0.9637 7.7970 0.8911 7.9562 7.9915 11.9505 12
0.8025 0.9304 7.9562 0.8911 8.0151 8.1094 11.9109 13
0.7650 0.9143 8.1565 0.8911 8.2567 8.3687 11.9257 14
0.7276 0.8825 8.1565 0.8911 8.2567 8.3687 11.9059 15
0.6877 0.8607 8.1565 0.8911 8.2567 8.3687 11.9257 16
0.6566 0.8303 8.1565 0.8911 8.2567 8.3687 11.9257 17
0.6205 0.8124 8.1565 0.8911 8.2567 8.3687 11.9307 18
0.5878 0.7924 8.1565 0.8911 8.2567 8.3687 11.9257 19
0.5535 0.7724 8.1565 0.8911 8.2567 8.3687 11.8911 20
0.5243 0.7751 8.1565 0.8911 8.2567 8.3687 11.9109 21
0.5444 0.8057 8.1565 0.8911 8.2567 8.3687 11.8911 22
0.5281 0.7875 8.1565 0.8911 8.2567 8.3687 11.8663 23
0.4990 0.7810 8.1565 0.8911 8.2567 8.3687 11.8762 24
0.4762 0.7858 8.6516 0.8911 8.6634 8.8579 11.8812 25
0.4538 0.7793 8.6516 0.8911 8.6634 8.8579 11.9158 26
0.4330 0.7813 8.6516 0.8911 8.6634 8.8579 11.8762 27
0.4142 0.7725 8.6516 0.8911 8.6634 8.8579 11.9307 28
0.3928 0.7920 8.6516 0.8911 8.6634 8.8579 11.9109 29

Framework versions

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