distilbert_oscarth_0060

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: 1.1876
• Validation Loss: 1.1378
• Epoch: 59

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': 'AdamWeightDecay', 'learning_rate': 2e-05, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-07, 'amsgrad': False, 'weight_decay_rate': 0.01}
• training_precision: float32

Training results

Train Loss	Validation Loss	Epoch
4.1327	2.9983	0
2.7813	2.4562	1
2.4194	2.2066	2
2.2231	2.0562	3
2.0894	1.9450	4
1.9905	1.8621	5
1.9148	1.7941	6
1.8508	1.7363	7
1.7976	1.6909	8
1.7509	1.6488	9
1.7126	1.6124	10
1.6764	1.5835	11
1.6450	1.5521	12
1.6175	1.5282	13
1.5919	1.5045	14
1.5679	1.4833	15
1.5476	1.4627	16
1.5271	1.4498	17
1.5098	1.4270	18
1.4909	1.4161	19
1.4760	1.3995	20
1.4609	1.3864	21
1.4475	1.3717	22
1.4333	1.3590	23
1.4203	1.3478	24
1.4093	1.3403	25
1.3980	1.3296	26
1.3875	1.3176	27
1.3773	1.3094	28
1.3674	1.3011	29
1.3579	1.2920	30
1.3497	1.2826	31
1.3400	1.2764	32
1.3326	1.2694	33
1.3236	1.2635	34
1.3169	1.2536	35
1.3096	1.2477	36
1.3024	1.2408	37
1.2957	1.2364	38
1.2890	1.2296	39
1.2818	1.2236	40
1.2751	1.2168	41
1.2691	1.2126	42
1.2644	1.2044	43
1.2583	1.2008	44
1.2529	1.1962	45
1.2473	1.1919	46
1.2416	1.1857	47
1.2365	1.1812	48
1.2318	1.1765	49
1.2273	1.1738	50
1.2224	1.1672	51
1.2177	1.1673	52
1.2132	1.1595	53
1.2084	1.1564	54
1.2033	1.1518	55
1.1993	1.1481	56
1.1966	1.1445	57
1.1924	1.1412	58
1.1876	1.1378	59

Framework versions

• Transformers 4.20.1
• TensorFlow 2.8.2
• Datasets 2.3.2
• Tokenizers 0.12.1