sevvalkapcak/newModel

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: 0.0146
• Validation Loss: 0.7180
• Train Accuracy: 0.909
• Epoch: 37

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': 5e-05, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False}
• training_precision: float32

Training results

Train Loss	Validation Loss	Train Accuracy	Epoch
0.0133	0.6573	0.901	0
0.0135	0.7314	0.9065	1
0.0104	0.6544	0.913	2
0.0148	0.7763	0.9035	3
0.0171	0.7110	0.9055	4
0.0121	0.7075	0.9015	5
0.0126	0.7461	0.8945	6
0.0212	0.7539	0.9035	7
0.0183	0.7842	0.9005	8
0.0192	0.7431	0.901	9
0.0224	0.6014	0.9065	10
0.0168	0.6000	0.914	11
0.0133	0.6241	0.9125	12
0.0097	0.6747	0.9075	13
0.0122	0.7352	0.908	14
0.0123	0.8061	0.905	15
0.0139	0.7254	0.8985	16
0.0120	0.6856	0.903	17
0.0175	0.6727	0.905	18
0.0155	0.6912	0.9055	19
0.0192	0.7535	0.903	20
0.0206	0.7428	0.8995	21
0.0108	0.7883	0.8965	22
0.0159	0.7443	0.8885	23
0.0238	0.7381	0.8935	24
0.0167	0.7888	0.901	25
0.0207	0.7062	0.899	26
0.0148	0.7670	0.9065	27
0.0177	0.6694	0.8925	28
0.0157	0.7312	0.9045	29
0.0145	0.6551	0.905	30
0.0188	0.7582	0.906	31
0.0136	0.7531	0.9085	32
0.0119	0.7965	0.8905	33
0.0069	0.8430	0.901	34
0.0100	0.7795	0.8975	35
0.0100	0.9567	0.889	36
0.0146	0.7180	0.909	37

Framework versions

• Transformers 4.35.2
• TensorFlow 2.15.0
• Datasets 2.16.1
• Tokenizers 0.15.1