transformer_QAVi / README.md
LongRiver's picture
Training in progress epoch 2
a6d2c5a
|
raw
history blame
2.61 kB
metadata
license: apache-2.0
base_model: distilbert-base-cased
tags:
  - generated_from_keras_callback
model-index:
  - name: LongRiver/transformer_QAVi
    results: []

LongRiver/transformer_QAVi

This model is a fine-tuned version of distilbert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:

  • Train Loss: 0.7229
  • Train End Logits Accuracy: 0.7909
  • Train Start Logits Accuracy: 0.7522
  • Validation Loss: 1.1848
  • Validation End Logits Accuracy: 0.6958
  • Validation Start Logits Accuracy: 0.6635
  • Epoch: 2

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': {'module': 'keras.optimizers.schedules', 'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 2e-05, 'decay_steps': 83175, '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}
  • training_precision: float32

Training results

Train Loss Train End Logits Accuracy Train Start Logits Accuracy Validation Loss Validation End Logits Accuracy Validation Start Logits Accuracy Epoch
1.5634 0.5935 0.5554 1.1964 0.6770 0.6480 0
0.9698 0.7308 0.6922 1.1189 0.7008 0.6740 1
0.7229 0.7909 0.7522 1.1848 0.6958 0.6635 2

Framework versions

  • Transformers 4.39.3
  • TensorFlow 2.15.0
  • Datasets 2.18.0
  • Tokenizers 0.15.2