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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: nerdylive/deberta-zeroshot |
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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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# nerdylive/deberta-zeroshot |
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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: 0.2575 |
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- Validation Loss: 0.1900 |
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- Train Accuracy: {'accuracy': 0.92612} |
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- Train F1 Score: {'f1': 0.9268080047553003} |
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- Train Precision: {'precision': 0.9182567726737338} |
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- Train Recall: {'recall': 0.93552} |
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- Epoch: 0 |
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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': 125000, '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 | Train F1 Score | Train Precision | Train Recall | Epoch | |
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|:----------:|:---------------:|:---------------------:|:--------------------------:|:---------------------------------:|:-------------------:|:-----:| |
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| 0.2575 | 0.1900 | {'accuracy': 0.92612} | {'f1': 0.9268080047553003} | {'precision': 0.9182567726737338} | {'recall': 0.93552} | 0 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- TensorFlow 2.12.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.13.3 |
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