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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: ratish/DBERT_CleanDesc_v2 |
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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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# ratish/DBERT_CleanDesc_v2 |
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-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: 0.0738 |
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- Validation Loss: 0.6606 |
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- Train Accuracy: 0.85 |
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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': 'Adam', 'weight_decay': None, 'clipnorm': None, 'global_clipnorm': None, 'clipvalue': None, 'use_ema': False, 'ema_momentum': 0.99, 'ema_overwrite_frequency': None, 'jit_compile': True, 'is_legacy_optimizer': False, 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 6180, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False} |
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- training_precision: float32 |
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### Training results |
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| Train Loss | Validation Loss | Train Accuracy | Epoch | |
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|:----------:|:---------------:|:--------------:|:-----:| |
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| 2.2247 | 2.0414 | 0.375 | 0 | |
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| 1.6722 | 1.6034 | 0.575 | 1 | |
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| 1.2412 | 1.3270 | 0.6 | 2 | |
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| 0.9495 | 1.0999 | 0.6 | 3 | |
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| 0.7464 | 0.9892 | 0.65 | 4 | |
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| 0.6087 | 0.8445 | 0.75 | 5 | |
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| 0.4628 | 0.8918 | 0.7 | 6 | |
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| 0.3747 | 0.7971 | 0.775 | 7 | |
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| 0.3069 | 0.7776 | 0.75 | 8 | |
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| 0.2492 | 0.6877 | 0.825 | 9 | |
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| 0.2148 | 0.7085 | 0.8 | 10 | |
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| 0.1793 | 0.6896 | 0.85 | 11 | |
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| 0.1598 | 0.7230 | 0.85 | 12 | |
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| 0.1308 | 0.7365 | 0.85 | 13 | |
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| 0.1211 | 0.6985 | 0.85 | 14 | |
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| 0.1023 | 0.6592 | 0.85 | 15 | |
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| 0.0892 | 0.6621 | 0.85 | 16 | |
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| 0.0885 | 0.6387 | 0.85 | 17 | |
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| 0.0738 | 0.6606 | 0.85 | 18 | |
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### Framework versions |
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- Transformers 4.27.4 |
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- TensorFlow 2.12.0 |
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- Datasets 2.11.0 |
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- Tokenizers 0.13.3 |
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