adelinachirtes commited on
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Training in progress epoch 0

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  1. README.md +15 -21
  2. config.json +0 -2
  3. tf_model.h5 +3 -0
README.md CHANGED
@@ -2,23 +2,23 @@
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  license: apache-2.0
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  base_model: distilbert/distilbert-base-uncased
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  tags:
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- - generated_from_trainer
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- metrics:
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- - accuracy
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  model-index:
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- - name: my_awesome_model
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  results: []
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  ---
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- <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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- should probably proofread and complete it, then remove this comment. -->
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- # my_awesome_model
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  This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2309
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- - Accuracy: 0.9312
 
 
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  ## Model description
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@@ -37,25 +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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- - learning_rate: 2e-05
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- - train_batch_size: 16
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- - eval_batch_size: 16
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- - seed: 42
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- - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- - lr_scheduler_type: linear
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- - num_epochs: 2
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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- |:-------------:|:-----:|:----:|:---------------:|:--------:|
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- | 0.2225 | 1.0 | 1563 | 0.2090 | 0.9216 |
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- | 0.1467 | 2.0 | 3126 | 0.2309 | 0.9312 |
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  ### Framework versions
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  - Transformers 4.41.1
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- - Pytorch 2.3.0+cu121
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  - Datasets 2.19.1
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  - Tokenizers 0.19.1
 
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  license: apache-2.0
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  base_model: distilbert/distilbert-base-uncased
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  tags:
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+ - generated_from_keras_callback
 
 
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  model-index:
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+ - name: adelinachirtes/my_awesome_model
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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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+ # adelinachirtes/my_awesome_model
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  This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
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  It achieves the following results on the evaluation set:
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+ - Train Loss: 0.2559
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+ - Validation Loss: 0.1899
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+ - Train Accuracy: 0.9283
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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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 7810, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'registered_name': None}, '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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+ | 0.2559 | 0.1899 | 0.9283 | 0 |
 
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  ### Framework versions
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  - Transformers 4.41.1
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+ - TensorFlow 2.15.0
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  - Datasets 2.19.1
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  - Tokenizers 0.19.1
config.json CHANGED
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  "n_heads": 12,
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  "n_layers": 6,
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  "pad_token_id": 0,
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- "problem_type": "single_label_classification",
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  "qa_dropout": 0.1,
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  "seq_classif_dropout": 0.2,
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  "sinusoidal_pos_embds": false,
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  "tie_weights_": true,
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- "torch_dtype": "float32",
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  "transformers_version": "4.41.1",
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  "vocab_size": 30522
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  }
 
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  "n_heads": 12,
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  "n_layers": 6,
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  "pad_token_id": 0,
 
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  "qa_dropout": 0.1,
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  "seq_classif_dropout": 0.2,
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  "sinusoidal_pos_embds": false,
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  "tie_weights_": true,
 
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  "transformers_version": "4.41.1",
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  "vocab_size": 30522
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  }
tf_model.h5 ADDED
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