README.md

metadata

license: apache-2.0
tags:
  - generated_from_keras_callback
model-index:
  - name: Regression_bert_1
    results: []

Regression_bert_1

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

• Train Loss: 0.3594
• Train Mae: 0.2822
• Train Mse: 0.1206
• Train R2-score: 0.6163
• Train Accuracy: 0.5308
• Validation Loss: 0.3503
• Validation Mae: 0.3488
• Validation Mse: 0.1574
• Validation R2-score: 0.8718
• Validation Accuracy: 0.2703
• Epoch: 9

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': 2e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
• training_precision: float32

Training results

Train Loss	Train Mae	Train Mse	Train R2-score	Train Accuracy	Validation Loss	Validation Mae	Validation Mse	Validation R2-score	Validation Accuracy	Epoch
0.4941	0.2941	0.1183	-0.5444	0.5769	0.3126	0.3108	0.1099	0.8865	0.2703	0
0.4660	0.3256	0.1546	0.0002	0.5231	0.3682	0.3669	0.1835	0.8572	0.2703	1
0.4110	0.3178	0.1552	0.6834	0.5	0.4381	0.4369	0.2390	0.8207	0.2703	2
0.3886	0.3112	0.1560	0.7184	0.5231	0.3566	0.3552	0.1672	0.8661	0.2703	3
0.4055	0.2890	0.1248	0.7655	0.6077	0.4364	0.4353	0.2376	0.8218	0.2703	4
0.3955	0.2930	0.1272	0.7685	0.5538	0.3868	0.3855	0.1971	0.8489	0.2703	5
0.3949	0.3003	0.1386	0.3857	0.5154	0.3614	0.3600	0.1751	0.8620	0.2703	6
0.3390	0.2874	0.1306	0.7121	0.5231	0.3766	0.3753	0.1894	0.8542	0.2703	7
0.3556	0.2775	0.1190	0.7890	0.5231	0.3561	0.3547	0.1664	0.8667	0.2703	8
0.3594	0.2822	0.1206	0.6163	0.5308	0.3503	0.3488	0.1574	0.8718	0.2703	9

Framework versions

• Transformers 4.27.2
• TensorFlow 2.11.0
• Datasets 2.10.1
• Tokenizers 0.13.2