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Upload TFDistilBertForTokenClassification

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  1. README.md +60 -0
  2. config.json +285 -0
  3. tf_model.h5 +3 -0
README.md ADDED
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+ ---
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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: baseline_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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+ # baseline_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: 0.1997
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+ - Validation Loss: 0.2418
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+ - Train Precision: 0.8722
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+ - Train Recall: 0.8725
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+ - Train F1: 0.8723
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+ - Train Accuracy: 0.9536
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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': 'AdamWeightDecay', 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 927, '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, 'weight_decay_rate': 0.01}
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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 | Validation Loss | Train Precision | Train Recall | Train F1 | Train Accuracy | Epoch |
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+ |:----------:|:---------------:|:---------------:|:------------:|:--------:|:--------------:|:-----:|
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+ | 0.9511 | 0.3933 | 0.8058 | 0.7913 | 0.7985 | 0.9267 | 0 |
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+ | 0.2735 | 0.2720 | 0.8628 | 0.8628 | 0.8628 | 0.9509 | 1 |
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+ | 0.1997 | 0.2418 | 0.8722 | 0.8725 | 0.8723 | 0.9536 | 2 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.41.2
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+ - TensorFlow 2.16.1
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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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+ "DistilBertForTokenClassification"
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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": "O",
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+ "1": "B-meal_description",
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+ "2": "B-or",
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+ "3": "I-depart_time.period_of_day",
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+ "4": "B-depart_time.time",
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+ "6": "I-depart_time.time_relative",
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+ "7": "B-airline_code",
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+ "8": "B-airport_code",
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+ "9": "B-aircraft_code",
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+ "12": "I-stoploc.city_name",
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+ "14": "I-transport_type",
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+ "16": "B-meal_code",
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+ "19": "I-cost_relative",
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+ "21": "B-depart_time.start_time",
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+ "22": "I-arrive_time.time",
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+ "42": "B-fare_amount",
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+ "44": "B-stoploc.airport_name",
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+ "49": "I-state_name",
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+ "50": "I-arrive_date.day_number",
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+ "51": "B-class_type",
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+ "52": "I-economy",
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+ "53": "I-round_trip",
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+ "54": "B-arrive_date.month_name",
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+ "55": "B-depart_date.day_number",
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+ "56": "I-fromloc.state_name",
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+ "57": "B-depart_date.month_name",
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+ "58": "I-class_type",
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+ "64": "I-return_date.date_relative",
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+ }
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