huynhdoo commited on
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Training in progress epoch 0

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README.md CHANGED
@@ -14,11 +14,11 @@ probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [camembert-base](https://huggingface.co/camembert-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Train Loss: 0.0542
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- - Train Accuracy: 0.9844
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- - Validation Loss: 0.5073
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- - Validation Accuracy: 0.8436
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- - Epoch: 4
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  ## Model description
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@@ -37,23 +37,19 @@ More information needed
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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': 5e-05, 'decay_steps': 1005, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, '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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- | 0.4753 | 0.7890 | 0.3616 | 0.8547 | 0 |
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- | 0.3120 | 0.8799 | 0.3702 | 0.8492 | 1 |
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- | 0.1824 | 0.9340 | 0.3928 | 0.8547 | 2 |
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- | 0.0972 | 0.9714 | 0.4849 | 0.8436 | 3 |
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- | 0.0542 | 0.9844 | 0.5073 | 0.8436 | 4 |
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  ### Framework versions
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  - Transformers 4.26.1
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  - TensorFlow 2.11.0
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- - Datasets 2.9.0
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  - Tokenizers 0.13.2
 
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  This model is a fine-tuned version of [camembert-base](https://huggingface.co/camembert-base) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Train Loss: 0.5259
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+ - Train Accuracy: 0.7349
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+ - Validation Loss: 0.4369
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+ - Validation Accuracy: 0.8017
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+ - Epoch: 0
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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': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 2838, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, '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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+ | 0.5259 | 0.7349 | 0.4369 | 0.8017 | 0 |
 
 
 
 
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  ### Framework versions
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  - Transformers 4.26.1
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  - TensorFlow 2.11.0
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+ - Datasets 2.10.1
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  - Tokenizers 0.13.2
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