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--- |
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license: apache-2.0 |
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base_model: google/flan-t5-small |
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tags: |
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- generated_from_keras_callback |
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model-index: |
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- name: t5-small-trivia-gpu-c2a |
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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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# t5-small-trivia-gpu-c2a |
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This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co./google/flan-t5-small) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Train Loss: 0.6412 |
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- Validation Loss: 0.8149 |
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- Epoch: 1 |
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<pre>{'eval_loss': 0.7876685857772827, |
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'eval_bleu': 35.10848749144238, |
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'eval_rouge1': 46.59, |
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'eval_rouge2': 22.34, |
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'eval_rougeL': 46.62, |
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'eval_rougeLsum': 46.58, |
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'eval_exact': 0.41599455835195803, |
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'eval_runtime': 175.9461, |
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'eval_samples_per_second': 58.489, |
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'eval_steps_per_second': 1.83} |
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</pre> |
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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': 'Adafactor', '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': 0.001, 'beta_2_decay': -0.8, 'epsilon_1': 1e-30, 'epsilon_2': 0.001, 'clip_threshold': 1.0, 'relative_step': False} |
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- training_precision: float32 |
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### Training results |
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| Train Loss | Validation Loss | Epoch | |
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|:----------:|:---------------:|:-----:| |
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| 0.9503 | 0.7819 | 0 | |
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| 0.6412 | 0.8149 | 1 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- TensorFlow 2.13.0 |
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- Datasets 2.14.3 |
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- Tokenizers 0.13.3 |
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