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library_name: transformers
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license: apache-2.0
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base_model: distilbert-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: tl-test-learn-prompt-classifier
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results: []
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---
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library_name: transformers
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license: apache-2.0
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base_model: distilbert-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: tl-test-learn-prompt-classifier
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results: []
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datasets:
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- reddgr/tl-test-learn-prompts
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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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# tl-test-learn-prompt-classifier
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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: 0.1733
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- Train Accuracy: 0.9756
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- Validation Loss: 0.3006
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- Validation Accuracy: 0.8977
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- Epoch: 6
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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': False, 'is_legacy_optimizer': False, 'learning_rate': 5e-06, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
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- training_precision: float32
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### Training results
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| Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
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|:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
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| 0.6870 | 0.5707 | 0.6656 | 0.6136 | 0 |
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| 0.6542 | 0.6293 | 0.6289 | 0.6477 | 1 |
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| 0.5970 | 0.7902 | 0.5541 | 0.7955 | 2 |
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| 0.4936 | 0.8829 | 0.4490 | 0.8523 | 3 |
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| 0.3649 | 0.9415 | 0.3775 | 0.875 | 4 |
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| 0.2563 | 0.9561 | 0.3254 | 0.8977 | 5 |
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| 0.1733 | 0.9756 | 0.3006 | 0.8977 | 6 |
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### Framework versions
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- Transformers 4.44.2
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- TensorFlow 2.18.0-dev20240717
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- Datasets 2.21.0
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- Tokenizers 0.19.1
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