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--- |
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license: apache-2.0 |
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base_model: bert-large-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: vedantjumle/bert-2 |
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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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# vedantjumle/bert-2 |
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This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 4.4459 |
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- Validation Loss: 4.3669 |
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- Train Accuracy: 0.0233 |
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- Epoch: 25 |
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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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 6000, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_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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| 5.1229 | 5.0343 | 0.0067 | 0 | |
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| 5.0629 | 5.0547 | 0.0033 | 1 | |
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| 5.0585 | 5.0239 | 0.0167 | 2 | |
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| 5.0530 | 5.0257 | 0.0167 | 3 | |
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| 5.0545 | 5.0207 | 0.01 | 4 | |
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| 5.0549 | 5.0104 | 0.01 | 5 | |
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| 5.0401 | 5.0240 | 0.0067 | 6 | |
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| 5.0400 | 5.0121 | 0.01 | 7 | |
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| 5.0372 | 5.0030 | 0.0167 | 8 | |
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| 5.0326 | 5.0256 | 0.0067 | 9 | |
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| 5.0382 | 4.9992 | 0.01 | 10 | |
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| 5.0144 | 4.9976 | 0.01 | 11 | |
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| 5.0152 | 4.9783 | 0.0167 | 12 | |
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| 4.9700 | 4.9433 | 0.0067 | 13 | |
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| 4.9206 | 4.9482 | 0.0067 | 14 | |
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| 4.9153 | 4.8727 | 0.0067 | 15 | |
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| 4.9287 | 4.7980 | 0.0167 | 16 | |
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| 4.8014 | 4.7452 | 0.0167 | 17 | |
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| 4.7477 | 4.6429 | 0.01 | 18 | |
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| 4.6939 | 4.6035 | 0.02 | 19 | |
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| 4.6607 | 4.5406 | 0.02 | 20 | |
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| 4.6075 | 4.5490 | 0.0167 | 21 | |
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| 4.5748 | 4.5086 | 0.0333 | 22 | |
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| 4.5383 | 4.3940 | 0.0333 | 23 | |
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| 4.4965 | 4.3748 | 0.0233 | 24 | |
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| 4.4459 | 4.3669 | 0.0233 | 25 | |
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### Framework versions |
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- Transformers 4.34.0 |
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- TensorFlow 2.13.0 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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