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Upload TFDistilBertForSequenceClassification

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  1. README.md +59 -0
  2. config.json +31 -0
  3. tf_model.h5 +3 -0
README.md ADDED
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+ ---
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+ library_name: transformers
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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: Fake_News_Bert_Model
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+ results: []
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+ ---
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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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+
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+ # Fake_News_Bert_Model
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+
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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: 0.2033
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+ - Train Accuracy: 0.9550
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+ - Validation Loss: 0.2320
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+ - Validation Accuracy: 0.9223
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+ - Epoch: 2
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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': False, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 2060, '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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+
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+ ### Training results
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+
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+ | Train Loss | Train Accuracy | Validation Loss | Validation Accuracy | Epoch |
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+ |:----------:|:--------------:|:---------------:|:-------------------:|:-----:|
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+ | 0.6163 | 0.6575 | 0.4918 | 0.8350 | 0 |
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+ | 0.4170 | 0.8525 | 0.2744 | 0.9320 | 1 |
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+ | 0.2033 | 0.9550 | 0.2320 | 0.9223 | 2 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.45.2
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+ - TensorFlow 2.16.2
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+ - Datasets 3.0.1
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+ - Tokenizers 0.20.1
config.json ADDED
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+ {
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+ "_name_or_path": "distilbert/distilbert-base-uncased",
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+ "activation": "gelu",
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+ "architectures": [
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+ "DistilBertForSequenceClassification"
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+ ],
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+ "attention_dropout": 0.1,
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+ "dim": 768,
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+ "dropout": 0.1,
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+ "hidden_dim": 3072,
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+ "id2label": {
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+ "0": "Real",
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+ "1": "Fake"
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+ },
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+ "initializer_range": 0.02,
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+ "label2id": {
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+ "Fake": 1,
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+ "Real": 0
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+ },
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+ "max_position_embeddings": 512,
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+ "model_type": "distilbert",
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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": "4.45.2",
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+ "vocab_size": 30522
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+ }
tf_model.h5 ADDED
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