vladjr commited on
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Training in progress epoch 0

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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: google/electra-base-discriminator
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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/electra-teste
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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/electra-teste
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+
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+ This model is a fine-tuned version of [google/electra-base-discriminator](https://huggingface.co/google/electra-base-discriminator) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Train Loss: 3.0564
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+ - Validation Loss: 1.7752
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+ - Train Accuracy: 0.8333
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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': 2100, '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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+ | 3.0564 | 1.7752 | 0.8333 | 0 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.34.0
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+ - TensorFlow 2.13.0
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+ - Datasets 2.14.5
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+ - Tokenizers 0.14.1
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+ {
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+ "_name_or_path": "google/electra-base-discriminator",
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+ "architectures": [
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+ "ElectraForSequenceClassification"
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+ ],
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+ "attention_probs_dropout_prob": 0.1,
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+ "hidden_act": "gelu",
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+ "hidden_dropout_prob": 0.1,
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+ "id2label": {
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+ "0": "Alternative Investment",
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+ "1": "Appreciative Inquiry",
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+ "2": "Artificial Intelligence",
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+ "3": "Accounts Receivable",
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+ "4": "Annual Review",
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+ "5": "Applicant Tracking System",
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+ "6": "Automated Trading System",
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+ "7": "Career Advancement",
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+ "8": "Chartered Accountant",
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+ "9": "Customer Acquisition",
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+ "10": "Career Pathing",
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+ "12": "Cost Per Mille",
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+ "14": "Credit Risk Management",
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+ "18": "Diversity, Equity, and Inclusion",
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+ "20": "Earnings Report",
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+ "21": "Employee Relations",
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+ "23": "Employee Value Proposition",
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+ "24": "Executive Vice President",
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+ "25": "Marketing Automation",
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+ "26": "Mergers & Acquisitions",
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+ "27": "Management BuyOut",
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+ "36": "Return on Investment",
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+ "37": "Return on Involvement",
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+ "38": "Recruitment Process Outsourcing",
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+ "39": "Request for Purchase Order",
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+ "41": "Small and Medium-sized Enterprises",
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+ "42": "Subject Matter Expert"
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