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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_ZS_CleanCollision_v1 |
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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_ZS_CleanCollision_v1 |
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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: 0.0014 |
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- Validation Loss: 0.0010 |
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- Train Accuracy: 1.0 |
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- Epoch: 27 |
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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': 9960, '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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| 0.7535 | 0.3396 | 1.0 | 0 | |
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| 0.2209 | 0.0995 | 1.0 | 1 | |
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| 0.0806 | 0.0471 | 1.0 | 2 | |
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| 0.0450 | 0.0296 | 1.0 | 3 | |
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| 0.0305 | 0.0210 | 1.0 | 4 | |
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| 0.0222 | 0.0157 | 1.0 | 5 | |
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| 0.0175 | 0.0122 | 1.0 | 6 | |
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| 0.0139 | 0.0098 | 1.0 | 7 | |
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| 0.0111 | 0.0080 | 1.0 | 8 | |
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| 0.0094 | 0.0066 | 1.0 | 9 | |
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| 0.0077 | 0.0056 | 1.0 | 10 | |
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| 0.0067 | 0.0048 | 1.0 | 11 | |
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| 0.0059 | 0.0042 | 1.0 | 12 | |
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| 0.0053 | 0.0037 | 1.0 | 13 | |
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| 0.0044 | 0.0032 | 1.0 | 14 | |
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| 0.0041 | 0.0029 | 1.0 | 15 | |
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| 0.0036 | 0.0026 | 1.0 | 16 | |
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| 0.0032 | 0.0023 | 1.0 | 17 | |
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| 0.0029 | 0.0021 | 1.0 | 18 | |
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| 0.0027 | 0.0019 | 1.0 | 19 | |
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| 0.0024 | 0.0017 | 1.0 | 20 | |
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| 0.0022 | 0.0016 | 1.0 | 21 | |
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| 0.0020 | 0.0015 | 1.0 | 22 | |
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| 0.0018 | 0.0013 | 1.0 | 23 | |
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| 0.0017 | 0.0012 | 1.0 | 24 | |
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| 0.0016 | 0.0011 | 1.0 | 25 | |
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| 0.0015 | 0.0011 | 1.0 | 26 | |
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| 0.0014 | 0.0010 | 1.0 | 27 | |
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### Framework versions |
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- Transformers 4.28.1 |
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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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