christopheparisse commited on
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Upload TFFlaubertForSequenceClassification

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  1. README.md +3 -13
  2. config.json +1 -1
README.md CHANGED
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  ---
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- license: mit
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- base_model: flaubert/flaubert_base_cased
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  tags:
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  - generated_from_keras_callback
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  model-index:
@@ -13,12 +11,9 @@ probably proofread and complete it, then remove this comment. -->
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  # complexity_80_model
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- This model is a fine-tuned version of [flaubert/flaubert_base_cased](https://huggingface.co/flaubert/flaubert_base_cased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Train Loss: 0.1458
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- - Validation Loss: 0.1550
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- - Train Accuracy: 0.9328
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- - Epoch: 2
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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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 196040, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
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  - training_precision: float32
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  ### Training results
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- | Train Loss | Validation Loss | Train Accuracy | Epoch |
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- |:----------:|:---------------:|:--------------:|:-----:|
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- | 0.1899 | 0.1728 | 0.9235 | 0 |
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- | 0.1619 | 0.1627 | 0.9315 | 1 |
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- | 0.1458 | 0.1550 | 0.9328 | 2 |
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  ### Framework versions
 
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  ---
 
 
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  tags:
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  - generated_from_keras_callback
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  model-index:
 
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  # complexity_80_model
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+ This model was trained from scratch on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+
 
 
 
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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: None
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  - training_precision: float32
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  ### Training results
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  ### Framework versions
config.json CHANGED
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  {
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- "_name_or_path": "flaubert/flaubert_base_cased",
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  "amp": 1,
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  "architectures": [
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  "FlaubertForSequenceClassification"
 
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  {
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+ "_name_or_path": "complexity_80_model",
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  "amp": 1,
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  "architectures": [
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  "FlaubertForSequenceClassification"