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--- |
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license: apache-2.0 |
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base_model: bert-base-uncased |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: node-py/my_awesome_eli5_clm-model |
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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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# node-py/my_awesome_eli5_clm-model |
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This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co./bert-base-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 2.2501 |
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- Validation Loss: 4.2690 |
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- Epoch: 35 |
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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 | Epoch | |
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|:----------:|:---------------:|:-----:| |
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| 7.3929 | 6.0819 | 0 | |
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| 5.9912 | 5.8303 | 1 | |
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| 5.7553 | 5.5854 | 2 | |
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| 5.5082 | 5.3645 | 3 | |
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| 5.2836 | 5.1815 | 4 | |
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| 5.0867 | 5.0252 | 5 | |
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| 4.9075 | 4.8834 | 6 | |
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| 4.7424 | 4.7747 | 7 | |
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| 4.5947 | 4.6684 | 8 | |
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| 4.4570 | 4.5836 | 9 | |
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| 4.3290 | 4.5194 | 10 | |
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| 4.2123 | 4.4408 | 11 | |
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| 4.1037 | 4.3965 | 12 | |
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| 3.9979 | 4.3630 | 13 | |
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| 3.8983 | 4.3101 | 14 | |
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| 3.8011 | 4.2792 | 15 | |
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| 3.7097 | 4.2592 | 16 | |
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| 3.6182 | 4.2285 | 17 | |
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| 3.5337 | 4.2061 | 18 | |
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| 3.4483 | 4.1943 | 19 | |
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| 3.3589 | 4.1787 | 20 | |
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| 3.2776 | 4.1684 | 21 | |
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| 3.1959 | 4.1764 | 22 | |
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| 3.1161 | 4.1673 | 23 | |
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| 3.0389 | 4.1643 | 24 | |
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| 2.9631 | 4.1647 | 25 | |
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| 2.8859 | 4.1639 | 26 | |
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| 2.8110 | 4.1737 | 27 | |
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| 2.7362 | 4.1677 | 28 | |
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| 2.6631 | 4.1952 | 29 | |
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| 2.5915 | 4.2045 | 30 | |
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| 2.5227 | 4.1999 | 31 | |
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| 2.4573 | 4.2159 | 32 | |
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| 2.3862 | 4.2372 | 33 | |
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| 2.3205 | 4.2358 | 34 | |
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| 2.2501 | 4.2690 | 35 | |
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### Framework versions |
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- Transformers 4.44.0 |
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- TensorFlow 2.16.1 |
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- Datasets 2.21.0 |
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- Tokenizers 0.19.1 |
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