Labira/LabiraPJOK_3_100_Full

This model is a fine-tuned version of Labira/LabiraPJOK_2_100_Full on an unknown dataset. It achieves the following results on the evaluation set:

• Train Loss: 0.0019
• Validation Loss: 0.0005
• Epoch: 98

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': 1100, '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	Validation Loss	Epoch
2.7614	1.1522	0
1.5531	0.5524	1
1.0482	0.2232	2
0.5443	0.0847	3
0.5227	0.0529	4
0.2873	0.0412	5
0.2568	0.0330	6
0.1310	0.0190	7
0.1108	0.0067	8
0.1252	0.0117	9
0.0740	0.0071	10
0.0507	0.0059	11
0.0790	0.0058	12
0.0282	0.0036	13
0.0562	0.0070	14
0.0850	0.0047	15
0.0715	0.0176	16
0.0724	0.0077	17
0.0361	0.0024	18
0.0266	0.0029	19
0.0207	0.0026	20
0.0158	0.0023	21
0.0086	0.0016	22
0.0214	0.0093	23
0.0327	0.0063	24
0.0102	0.0016	25
0.0072	0.0012	26
0.0273	0.0024	27
0.0185	0.0034	28
0.0091	0.0018	29
0.0144	0.0021	30
0.0107	0.0032	31
0.0632	0.0037	32
0.0149	0.0034	33
0.0151	0.0103	34
0.0195	0.0081	35
0.0145	0.0023	36
0.0150	0.0012	37
0.0126	0.0018	38
0.0068	0.0017	39
0.0057	0.0014	40
0.0075	0.0015	41
0.0035	0.0015	42
0.0059	0.0013	43
0.0040	0.0010	44
0.0036	0.0009	45
0.0040	0.0011	46
0.0058	0.0020	47
0.0801	0.0013	48
0.0062	0.0014	49
0.0049	0.0011	50
0.0057	0.0012	51
0.0023	0.0011	52
0.0047	0.0007	53
0.0041	0.0006	54
0.0056	0.0012	55
0.0035	0.0016	56
0.0042	0.0011	57
0.0029	0.0006	58
0.0025	0.0004	59
0.0229	0.0085	60
0.0057	0.0075	61
0.0038	0.0050	62
0.0047	0.0014	63
0.0024	0.0006	64
0.0021	0.0005	65
0.0480	0.0008	66
0.0041	0.0010	67
0.0038	0.0010	68
0.0032	0.0010	69
0.0037	0.0009	70
0.0027	0.0007	71
0.0041	0.0007	72
0.0039	0.0006	73
0.0024	0.0007	74
0.0020	0.0007	75
0.0026	0.0007	76
0.0058	0.0008	77
0.0025	0.0007	78
0.0021	0.0006	79
0.0028	0.0006	80
0.0024	0.0005	81
0.0015	0.0005	82
0.0100	0.0005	83
0.0018	0.0006	84
0.0039	0.0007	85
0.0019	0.0007	86
0.0022	0.0007	87
0.0021	0.0007	88
0.0025	0.0007	89
0.0014	0.0006	90
0.0014	0.0006	91
0.0038	0.0006	92
0.0024	0.0006	93
0.0017	0.0005	94
0.0020	0.0005	95
0.0030	0.0005	96
0.0032	0.0005	97
0.0019	0.0005	98

Framework versions

• Transformers 4.46.2
• TensorFlow 2.17.0
• Datasets 3.1.0
• Tokenizers 0.20.3