AIYIYA commited on
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Training in progress epoch 0

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Files changed (7) hide show
  1. README.md +54 -0
  2. config.json +74 -0
  3. special_tokens_map.json +7 -0
  4. tf_model.h5 +3 -0
  5. tokenizer.json +0 -0
  6. tokenizer_config.json +55 -0
  7. vocab.txt +0 -0
README.md ADDED
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+ ---
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+ base_model: bert-base-chinese
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+ tags:
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+ - generated_from_keras_callback
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+ model-index:
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+ - name: AIYIYA/my_new_inputs1
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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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+ # AIYIYA/my_new_inputs1
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+
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+ This model is a fine-tuned version of [bert-base-chinese](https://huggingface.co/bert-base-chinese) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Train Loss: 2.8547
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+ - Validation Loss: 2.5914
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+ - Train Accuracy: 0.4261
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+ - Epoch: 0
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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': 80, '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 | Validation Loss | Train Accuracy | Epoch |
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+ |:----------:|:---------------:|:--------------:|:-----:|
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+ | 2.8547 | 2.5914 | 0.4261 | 0 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - TensorFlow 2.15.0
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+ - Datasets 2.16.0
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+ - Tokenizers 0.15.0
config.json ADDED
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+ {
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+ "_name_or_path": "bert-base-chinese",
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+ "architectures": [
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+ "BertForSequenceClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "classifier_dropout": null,
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+ "directionality": "bidi",
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "hidden_size": 768,
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+ "id2label": {
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+ "0": "name",
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+ "1": "ssn",
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+ "2": "phone",
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+ "3": "email",
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+ "4": "date_of_birth",
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+ "5": "job",
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+ "6": "gender",
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+ "7": "nickname",
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+ "8": "address",
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+ "9": "company",
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+ "10": "bank",
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+ "11": "username",
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+ "12": "password",
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+ "13": "account",
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+ "14": "search",
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+ "15": "date",
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+ "16": "number",
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+ "17": "word",
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+ "18": "uri",
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+ "19": "yzm"
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+ },
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+ "initializer_range": 0.02,
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+ "intermediate_size": 3072,
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+ "label2id": {
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+ "account": 13,
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+ "address": 8,
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+ "bank": 10,
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+ "company": 9,
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+ "date": 15,
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+ "email": 3,
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+ "gender": 6,
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+ "job": 5,
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+ "nickname": 7,
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+ "number": 16,
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+ "password": 12,
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+ "search": 14,
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+ "ssn": 1,
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+ "uri": 18,
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+ "username": 11,
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+ "word": 17,
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+ "yzm": 19
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+ },
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+ "layer_norm_eps": 1e-12,
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+ "max_position_embeddings": 512,
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+ "model_type": "bert",
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+ "num_attention_heads": 12,
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+ "num_hidden_layers": 12,
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+ "pad_token_id": 0,
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+ "pooler_fc_size": 768,
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+ "pooler_num_attention_heads": 12,
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+ "pooler_num_fc_layers": 3,
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+ "pooler_size_per_head": 128,
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+ "pooler_type": "first_token_transform",
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+ "position_embedding_type": "absolute",
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+ "transformers_version": "4.35.2",
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+ "type_vocab_size": 2,
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+ "use_cache": true,
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+ "vocab_size": 21128
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+ }
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tokenizer.json ADDED
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tokenizer_config.json ADDED
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+ "tokenizer_class": "BertTokenizer",
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+ "unk_token": "[UNK]"
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+ }
vocab.txt ADDED
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