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Training in progress epoch 0

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README.md CHANGED
@@ -12,13 +12,13 @@ probably proofread and complete it, then remove this comment. -->
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  # huynhdoo/camembert-base-finetuned-jva-missions-report
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- This model is a fine-tuned version of [camembert-base](https://huggingface.co/camembert-base) on jva-missions-report dataset.
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  It achieves the following results on the evaluation set:
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- - Train Loss: 0.0877
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- - Train Accuracy: 0.9757
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- - Validation Loss: 0.5045
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  - Validation Accuracy: 0.8380
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- - Epoch: 4
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  ## Model description
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@@ -37,18 +37,14 @@ 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', '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}}, 'decay': 0.0, '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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- | 0.5060 | 0.7617 | 0.3795 | 0.8436 | 0 |
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- | 0.3267 | 0.8718 | 0.3577 | 0.8436 | 1 |
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- | 0.2134 | 0.9272 | 0.3967 | 0.8324 | 2 |
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- | 0.1303 | 0.9589 | 0.4488 | 0.8324 | 3 |
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- | 0.0877 | 0.9757 | 0.5045 | 0.8380 | 4 |
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  ### Framework versions
 
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  # huynhdoo/camembert-base-finetuned-jva-missions-report
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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: 0.4792
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+ - Train Accuracy: 0.7803
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+ - Validation Loss: 0.3889
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  - Validation Accuracy: 0.8380
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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', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5e-05, 'decay_steps': 201, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, '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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+ | 0.4792 | 0.7803 | 0.3889 | 0.8380 | 0 |
 
 
 
 
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  ### Framework versions
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