my-tweets-finetuned – AI Model by ashishbaraiya | AlphaNeural AI

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ashishbaraiya/
my-tweets-finetuned

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text-generation

generated_from_keras_callback

openai-community/gpt2

autotrain_compatible

endpoints_compatible

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ashishbaraiya/my-tweets-finetuned

This model is a fine-tuned version of gpt2 on an unknown dataset. It achieves the following results on the evaluation set:

Train Loss: 0.0656
Validation Loss: 3.2945
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': 5e-05, 'decay_steps': 4500, '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
9.3483	8.3624	0
7.2778	6.9685	1
5.9195	6.2234	2
5.0730	5.6830	3
4.4703	5.3916	4
3.8427	4.8847	5
3.3641	4.5318	6
2.8373	4.3084	7
2.4261	4.0802	8
2.0691	3.8920	9
1.8213	3.8208	10
1.5922	3.6103	11
1.3694	3.5038	12
1.1764	3.3149	13
1.0135	3.2981	14
0.8874	3.2975	15
0.7716	3.2103	16
0.6679	3.3297	17
0.5770	3.2517	18
0.5098	3.0959	19
0.4403	3.1526	20
0.3791	2.9750	21
0.3367	3.0588	22
0.3027	3.0408	23
0.2617	3.1930	24
0.2387	3.1227	25
0.2175	3.0582	26
0.2062	3.1239	27
0.1868	3.0407	28
0.1746	3.2357	29
0.1657	3.1285	30
0.1536	3.2110	31
0.1512	3.1890	32
0.1447	3.1713	33
0.1426	3.1498	34
0.1369	3.1877	35
0.1327	3.2019	36
0.1303	3.0486	37
0.1213	3.1264	38
0.1204	3.1468	39
0.1206	3.1846	40
0.1125	3.1880	41
0.1113	3.1980	42
0.1098	3.1759	43
0.1071	3.1385	44
0.1055	3.1730	45
0.1024	3.1820	46
0.0995	3.1252	47
0.0995	3.1279	48
0.1004	3.2428	49
0.0982	3.1116	50
0.0957	3.2210	51
0.0936	3.1351	52
0.0917	3.1618	53
0.0930	3.1924	54
0.0929	3.2831	55
0.0889	3.2458	56
0.0913	3.2061	57
0.0899	3.4128	58
0.0880	3.2114	59
0.0869	3.2738	60
0.0878	3.1723	61
0.0844	3.1465	62
0.0846	3.1106	63
0.0841	3.2216	64
0.0824	3.2971	65
0.0823	3.2267	66
0.0811	3.2503	67
0.0823	3.1981	68
0.0808	3.2618	69
0.0803	3.1607	70
0.0786	3.3295	71
0.0801	3.2952	72
0.0777	3.2545	73
0.0764	3.1248	74
0.0772	3.2185	75
0.0758	3.3147	76
0.0764	3.1842	77
0.0758	3.2346	78
0.0739	3.2914	79
0.0738	3.2163	80
0.0738	3.3555	81
0.0731	3.0948	82
0.0726	3.2040	83
0.0729	3.2187	84
0.0709	3.2877	85
0.0703	3.3668	86
0.0709	3.2290	87
0.0712	3.3148	88
0.0697	3.2762	89
0.0694	3.2083	90
0.0688	3.2673	91
0.0694	3.2816	92
0.0683	3.3135	93
0.0680	3.2971	94
0.0681	3.2272	95
0.0670	3.2317	96
0.0662	3.2029	97
0.0656	3.2945	98

Framework versions

Transformers 4.35.2
TensorFlow 2.15.0
Datasets 2.16.1
Tokenizers 0.15.1