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--- |
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license: apache-2.0 |
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base_model: google/mt5-base |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: pakawadeep/mt5-base-finetuned-ctfl-augmented_1 |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information Keras had access to. You should |
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probably proofread and complete it, then remove this comment. --> |
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# pakawadeep/mt5-base-finetuned-ctfl-augmented_1 |
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This model is a fine-tuned version of [google/mt5-base](https://huggingface.co/google/mt5-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.3060 |
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- Validation Loss: 0.7976 |
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- Train Rouge1: 8.9816 |
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- Train Rouge2: 1.2871 |
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- Train Rougel: 8.9463 |
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- Train Rougelsum: 8.9816 |
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- Train Gen Len: 11.8416 |
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- Epoch: 29 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- 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} |
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- training_precision: float32 |
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### Training results |
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| Train Loss | Validation Loss | Train Rouge1 | Train Rouge2 | Train Rougel | Train Rougelsum | Train Gen Len | Epoch | |
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|:----------:|:---------------:|:------------:|:------------:|:------------:|:---------------:|:-------------:|:-----:| |
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| 5.3770 | 2.6665 | 4.5262 | 0.6931 | 4.5733 | 4.5733 | 8.9356 | 0 | |
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| 2.7256 | 2.0063 | 5.6931 | 1.3201 | 5.6518 | 5.6931 | 10.2277 | 1 | |
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| 2.0053 | 1.4899 | 7.7086 | 2.1782 | 7.7086 | 7.7086 | 11.3465 | 2 | |
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| 1.5782 | 1.2268 | 7.7086 | 2.1782 | 7.7086 | 7.7086 | 11.8168 | 3 | |
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| 1.3143 | 1.1257 | 8.6987 | 2.1782 | 8.6987 | 8.4866 | 11.9257 | 4 | |
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| 1.1311 | 1.0411 | 8.9816 | 2.2772 | 8.9109 | 8.9109 | 11.9406 | 5 | |
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| 1.0120 | 0.9954 | 8.9816 | 2.2772 | 8.9109 | 8.9109 | 11.9406 | 6 | |
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| 0.9320 | 0.9375 | 8.9816 | 2.2772 | 8.9109 | 8.9109 | 11.9208 | 7 | |
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| 0.8538 | 0.8867 | 8.9816 | 2.2772 | 8.9109 | 8.9109 | 11.8911 | 8 | |
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| 0.7999 | 0.8593 | 8.8166 | 1.7822 | 8.7459 | 8.7459 | 11.8861 | 9 | |
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| 0.7562 | 0.8440 | 8.5573 | 1.2871 | 8.4866 | 8.5337 | 11.8812 | 10 | |
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| 0.7106 | 0.8085 | 8.5573 | 1.2871 | 8.4866 | 8.5337 | 11.8812 | 11 | |
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| 0.6685 | 0.8044 | 7.9562 | 0.7921 | 7.8147 | 7.9562 | 11.9059 | 12 | |
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| 0.6377 | 0.7867 | 8.4512 | 1.2871 | 8.4158 | 8.4512 | 11.8762 | 13 | |
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| 0.6067 | 0.7731 | 8.2980 | 0.7921 | 8.2096 | 8.2862 | 11.8960 | 14 | |
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| 0.5826 | 0.7593 | 8.2980 | 0.7921 | 8.2096 | 8.2862 | 11.8861 | 15 | |
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| 0.5533 | 0.7656 | 8.4512 | 1.2871 | 8.4158 | 8.4512 | 11.9010 | 16 | |
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| 0.5286 | 0.7657 | 8.4512 | 1.2871 | 8.4158 | 8.4512 | 11.8812 | 17 | |
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| 0.5049 | 0.7674 | 8.4512 | 1.2871 | 8.4158 | 8.4512 | 11.8465 | 18 | |
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| 0.4800 | 0.7591 | 8.4512 | 1.2871 | 8.4158 | 8.4512 | 11.8663 | 19 | |
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| 0.4593 | 0.7637 | 8.4512 | 1.2871 | 8.4158 | 8.4512 | 11.8663 | 20 | |
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| 0.4362 | 0.7757 | 8.4512 | 1.2871 | 8.4158 | 8.4512 | 11.8762 | 21 | |
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| 0.4185 | 0.7640 | 8.9816 | 1.2871 | 8.9463 | 8.9816 | 11.8812 | 22 | |
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| 0.4001 | 0.7496 | 8.9816 | 1.2871 | 8.9463 | 8.9816 | 11.8762 | 23 | |
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| 0.3826 | 0.7498 | 8.9816 | 1.2871 | 8.9463 | 8.9816 | 11.8515 | 24 | |
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| 0.3682 | 0.7646 | 8.9816 | 1.2871 | 8.9463 | 8.9816 | 11.8861 | 25 | |
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| 0.3525 | 0.7656 | 8.9816 | 1.2871 | 8.9463 | 8.9816 | 11.8762 | 26 | |
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| 0.3352 | 0.7774 | 9.0877 | 1.3861 | 8.9816 | 9.0347 | 11.9010 | 27 | |
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| 0.3208 | 0.7929 | 8.9816 | 1.2871 | 8.9463 | 8.9816 | 11.8960 | 28 | |
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| 0.3060 | 0.7976 | 8.9816 | 1.2871 | 8.9463 | 8.9816 | 11.8416 | 29 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- TensorFlow 2.15.0 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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