reddgr's picture
Upload TFDistilBertForSequenceClassification
9aa7918 verified
metadata
library_name: transformers
license: apache-2.0
base_model: distilbert-base-uncased
tags:
  - generated_from_keras_callback
model-index:
  - name: tl-test-learn-prompt-classifier
    results: []

tl-test-learn-prompt-classifier

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

  • Train Loss: 0.0934
  • Train Accuracy: 0.9923
  • Validation Loss: 0.2064
  • Validation Accuracy: 0.9196
  • Epoch: 7

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': False, 'is_legacy_optimizer': False, 'learning_rate': 5e-06, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
  • training_precision: float32

Training results

Train Loss Train Accuracy Validation Loss Validation Accuracy Epoch
0.6893 0.5367 0.6705 0.5536 0
0.6573 0.6911 0.6171 0.8125 1
0.5946 0.7876 0.5066 0.9196 2
0.4681 0.9035 0.3703 0.9107 3
0.3276 0.9266 0.2682 0.9286 4
0.2147 0.9614 0.2311 0.9196 5
0.1356 0.9768 0.2067 0.9286 6
0.0934 0.9923 0.2064 0.9196 7

Framework versions

  • Transformers 4.44.2
  • TensorFlow 2.18.0-dev20240717
  • Datasets 2.21.0
  • Tokenizers 0.19.1