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--- |
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license: mit |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: gpt_image_clef1 |
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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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# gpt_image_clef1 |
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This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 1.1002 |
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- Train Rouge: 0.4943 |
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- Validation Loss: 0.9385 |
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- Validation Rouge: 0.4581 |
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- Epoch: 8 |
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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': 'AdamWeightDecay', 'learning_rate': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 0.0005, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 0.0005, 'decay_steps': 2554800, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, '__passive_serialization__': True}, 'warmup_steps': 1000, 'power': 1.0, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.99, 'epsilon': 0.2, 'amsgrad': False, 'weight_decay_rate': 0.01} |
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- training_precision: float32 |
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### Training results |
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| Train Loss | Train Rouge | Validation Loss | Validation Rouge | Epoch | |
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|:----------:|:-----------:|:---------------:|:----------------:|:-----:| |
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| 1.5411 | 0.4201 | 1.0250 | 0.4297 | 0 | |
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| 1.1803 | 0.4674 | 0.9795 | 0.4437 | 1 | |
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| 1.1391 | 0.4801 | 0.9588 | 0.4523 | 2 | |
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| 1.1168 | 0.4869 | 0.9395 | 0.4590 | 3 | |
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| 1.1038 | 0.4912 | 0.9318 | 0.4613 | 4 | |
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| 1.0971 | 0.4934 | 0.9305 | 0.4611 | 5 | |
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| 1.0949 | 0.4945 | 0.9287 | 0.4621 | 6 | |
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| 1.0965 | 0.4948 | 0.9313 | 0.4605 | 7 | |
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| 1.1002 | 0.4943 | 0.9385 | 0.4581 | 8 | |
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### Framework versions |
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- Transformers 4.28.1 |
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- TensorFlow 2.10.1 |
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- Datasets 2.11.0 |
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- Tokenizers 0.13.3 |
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