pakawadeep's picture
Training in progress epoch 14
336bda0
|
raw
history blame
3.41 kB
metadata
license: apache-2.0
base_model: google/mt5-base
tags:
  - generated_from_keras_callback
model-index:
  - name: pakawadeep/mt5-base-finetuned-ctfl-augmented
    results: []

pakawadeep/mt5-base-finetuned-ctfl-augmented

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: 0.8809
  • Validation Loss: 0.8625
  • Train Rouge1: 8.7459
  • Train Rouge2: 1.8812
  • Train Rougel: 8.6987
  • Train Rougelsum: 8.8166
  • Train Gen Len: 11.9257
  • Epoch: 14

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
6.9468 2.5770 1.3751 0.2405 1.3339 1.3916 8.5050 0
3.5520 2.0970 5.5693 0.8251 5.5487 5.6106 10.8564 1
2.7376 2.2001 5.1568 1.3201 4.9505 5.1155 10.0099 2
2.4757 1.8936 6.2706 1.1881 6.2235 6.3885 10.3614 3
2.1064 1.5432 7.4045 1.6832 7.2136 7.4116 11.1040 4
1.8167 1.3532 8.4866 2.1782 8.4158 8.6987 11.5644 5
1.6032 1.1789 8.6987 2.1782 8.4866 8.6987 11.8267 6
1.4351 1.1083 8.6987 2.1782 8.4866 8.6987 11.9059 7
1.3021 1.0607 8.9109 2.3762 8.8048 8.9816 11.9604 8
1.2060 1.0120 8.9109 2.3762 8.8048 8.9816 11.9455 9
1.1182 0.9736 8.6987 1.8812 8.6987 8.7694 11.9703 10
1.0551 0.9458 8.6987 1.8812 8.6987 8.7694 11.9406 11
0.9862 0.9170 8.5926 1.3861 8.5337 8.6516 11.9455 12
0.9324 0.8727 8.5101 1.3861 8.4807 8.5691 11.9208 13
0.8809 0.8625 8.7459 1.8812 8.6987 8.8166 11.9257 14

Framework versions

  • Transformers 4.38.2
  • TensorFlow 2.15.0
  • Datasets 2.18.0
  • Tokenizers 0.15.2