Edit model card

RafaelMayer/electra-copec-1

This model is a fine-tuned version of mrm8488/electricidad-base-discriminator on an unknown dataset. It achieves the following results on the evaluation set:

  • Train Loss: 0.7863
  • Validation Loss: 0.7271
  • Train Accuracy: 0.1765
  • Train Precision: [0.17647059 0. ]
  • Train Precision W: 0.0311
  • Train Recall: [1. 0.]
  • Train Recall W: 0.1765
  • Train F1: [0.3 0. ]
  • Train F1 W: 0.0529
  • Epoch: 1

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

  • 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': {'class_name': 'WarmUp', 'config': {'initial_learning_rate': 2e-05, 'decay_schedule_fn': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 35, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}, 'passive_serialization': True}, 'warmup_steps': 5, 'power': 1.0, 'name': None}}, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False}
  • training_precision: float32

Training results

Train Loss Validation Loss Train Accuracy Train Precision Train Precision W Train Recall Train Recall W Train F1 Train F1 W Epoch
0.7863 0.7271 0.1765 [0.17647059 0. ] 0.0311 [1. 0.] 0.1765 [0.3 0. ] 0.0529 1

Framework versions

  • Transformers 4.32.1
  • TensorFlow 2.12.0
  • Datasets 2.14.4
  • Tokenizers 0.13.3
Downloads last month
10
Inference Examples
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social visibility and check back later, or deploy to Inference Endpoints (dedicated) instead.

Model tree for RafaelMayer/electra-copec-1

Finetuned
(91)
this model