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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 |
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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 |
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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: 0.7157 |
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- Validation Loss: 0.7914 |
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- Train Rouge1: 8.4512 |
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- Train Rouge2: 1.3861 |
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- Train Rougel: 8.4158 |
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- Train Rougelsum: 8.4866 |
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- Train Gen Len: 11.9356 |
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- Epoch: 18 |
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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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| 6.9468 | 2.5770 | 1.3751 | 0.2405 | 1.3339 | 1.3916 | 8.5050 | 0 | |
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| 3.5520 | 2.0970 | 5.5693 | 0.8251 | 5.5487 | 5.6106 | 10.8564 | 1 | |
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| 2.7376 | 2.2001 | 5.1568 | 1.3201 | 4.9505 | 5.1155 | 10.0099 | 2 | |
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| 2.4757 | 1.8936 | 6.2706 | 1.1881 | 6.2235 | 6.3885 | 10.3614 | 3 | |
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| 2.1064 | 1.5432 | 7.4045 | 1.6832 | 7.2136 | 7.4116 | 11.1040 | 4 | |
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| 1.8167 | 1.3532 | 8.4866 | 2.1782 | 8.4158 | 8.6987 | 11.5644 | 5 | |
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| 1.6032 | 1.1789 | 8.6987 | 2.1782 | 8.4866 | 8.6987 | 11.8267 | 6 | |
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| 1.4351 | 1.1083 | 8.6987 | 2.1782 | 8.4866 | 8.6987 | 11.9059 | 7 | |
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| 1.3021 | 1.0607 | 8.9109 | 2.3762 | 8.8048 | 8.9816 | 11.9604 | 8 | |
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| 1.2060 | 1.0120 | 8.9109 | 2.3762 | 8.8048 | 8.9816 | 11.9455 | 9 | |
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| 1.1182 | 0.9736 | 8.6987 | 1.8812 | 8.6987 | 8.7694 | 11.9703 | 10 | |
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| 1.0551 | 0.9458 | 8.6987 | 1.8812 | 8.6987 | 8.7694 | 11.9406 | 11 | |
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| 0.9862 | 0.9170 | 8.5926 | 1.3861 | 8.5337 | 8.6516 | 11.9455 | 12 | |
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| 0.9324 | 0.8727 | 8.5101 | 1.3861 | 8.4807 | 8.5691 | 11.9208 | 13 | |
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| 0.8809 | 0.8625 | 8.7459 | 1.8812 | 8.6987 | 8.8166 | 11.9257 | 14 | |
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| 0.8334 | 0.8322 | 8.4512 | 1.3861 | 8.4158 | 8.4866 | 11.9307 | 15 | |
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| 0.7864 | 0.8009 | 7.9562 | 0.7921 | 7.7793 | 7.9915 | 11.9010 | 16 | |
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| 0.7542 | 0.8049 | 8.2744 | 0.7921 | 8.2390 | 8.3215 | 11.8465 | 17 | |
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| 0.7157 | 0.7914 | 8.4512 | 1.3861 | 8.4158 | 8.4866 | 11.9356 | 18 | |
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### Framework versions |
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- Transformers 4.38.2 |
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- TensorFlow 2.15.0 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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