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Training in progress epoch 0

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Files changed (7) hide show
  1. README.md +55 -0
  2. config.json +47 -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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+ license: apache-2.0
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+ base_model: bert-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: vladjr/bert-teste3
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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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+ # vladjr/bert-teste3
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+
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+ This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-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: 1.5134
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+ - Validation Loss: 0.6709
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+ - Train Accuracy: 0.9056
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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': True, 'is_legacy_optimizer': False, 'learning_rate': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 450, '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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+ | 1.5134 | 0.6709 | 0.9056 | 0 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.34.1
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+ - TensorFlow 2.13.0
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+ - Datasets 2.14.5
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+ - Tokenizers 0.14.1
config.json ADDED
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+ {
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+ "_name_or_path": "bert-base-uncased",
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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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+ "gradient_checkpointing": false,
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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": "Accounts Receivable",
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+ "1": "Artificial Intelligence",
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+ "2": "Chartered Accountant",
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+ "3": "Cost Per Mille",
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+ "4": "Cost Per Million",
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+ "5": "Management By Objectives",
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+ "6": "Public Relations",
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+ "7": "Return on Investment",
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+ "8": "Small and Medium-sized Enterprises"
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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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+ "Accounts Receivable": 0,
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+ "Artificial Intelligence": 1,
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+ "Chartered Accountant": 2,
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+ "Cost Per Mille": 3,
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+ "Cost Per Million": 4,
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+ "Management By Objectives": 5,
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+ "Public Relations": 6,
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+ "Return on Investment": 7,
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+ "Small and Medium-sized Enterprises": 8
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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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+ "position_embedding_type": "absolute",
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+ "transformers_version": "4.34.1",
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+ "type_vocab_size": 2,
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+ "use_cache": true,
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+ "vocab_size": 30522
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+ }
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tokenizer.json ADDED
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tokenizer_config.json ADDED
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+ "clean_up_tokenization_spaces": true,
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+ "cls_token": "[CLS]",
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+ "tokenizer_class": "BertTokenizer",
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+ }
vocab.txt ADDED
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