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Upload TFT5ForConditionalGeneration

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  1. README.md +5 -5
  2. tf_model.h5 +1 -1
README.md CHANGED
@@ -15,8 +15,8 @@ probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [t5-small](https://huggingface.co/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: 1.6544
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- - Validation Loss: 1.5734
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  - Epoch: 1
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  ## Model description
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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': 2e-05, '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 | Validation Loss | Epoch |
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  |:----------:|:---------------:|:-----:|
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- | 1.9033 | 1.6715 | 0 |
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- | 1.6544 | 1.5734 | 1 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [t5-small](https://huggingface.co/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: 1.4264
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+ - Validation Loss: 1.2768
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  - Epoch: 1
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  ## Model description
 
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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': 0.0002, '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 | Validation Loss | Epoch |
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  |:----------:|:---------------:|:-----:|
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+ | 1.6181 | 1.3981 | 0 |
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+ | 1.4264 | 1.2768 | 1 |
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  ### Framework versions
tf_model.h5 CHANGED
@@ -1,3 +1,3 @@
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