eng-limbu-t5-base-all-001 – AI Model by bedus-creation | AlphaNeural AI

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bedus-creation/
eng-limbu-t5-base-all-001

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text2text-generation

generated_from_keras_callback

bedus-creation/eng-limbu-t5-base-all-001

endpoints_compatible

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bedus-creation/eng-limbu-t5-base-all-001

This model is a fine-tuned version of bedus-creation/eng-limbu-t5-base-all-001 on an unknown dataset. It achieves the following results on the evaluation set:

Train Loss: 1.7242
Validation Loss: 2.6274
Epoch: 64

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
7.0062	6.1115	0
6.0720	5.8817	1
5.8833	5.7515	2
5.7643	5.6312	3
5.6159	5.5281	4
5.5133	5.4337	5
5.4239	5.3227	6
5.3002	5.2327	7
5.1915	5.1267	8
5.1029	5.0370	9
4.9916	4.9413	10
4.8633	4.8633	11
4.7651	4.7806	12
4.6682	4.7019	13
4.5570	4.6346	14
4.4718	4.5772	15
4.3830	4.5084	16
4.2749	4.4127	17
4.1922	4.3616	18
4.1207	4.3160	19
4.0164	4.2560	20
3.9700	4.1961	21
3.8745	4.1515	22
3.8068	4.0910	23
3.7149	4.0444	24
3.6474	3.9920	25
3.5522	3.9630	26
3.5127	3.8822	27
3.4414	3.8390	28
3.3722	3.7892	29
3.2981	3.7517	30
3.2240	3.7112	31
3.1878	3.6488	32
3.1070	3.6168	33
3.0528	3.5680	34
2.9806	3.5328	35
2.9294	3.4970	36
2.8907	3.4519	37
2.8304	3.4270	38
2.7737	3.3785	39
2.7023	3.3517	40
2.6705	3.3207	41
2.6218	3.2700	42
2.5651	3.2356	43
2.5065	3.2072	44
2.4517	3.1826	45
2.4043	3.1395	46
2.3662	3.0882	47
2.3240	3.0693	48
2.2801	3.0547	49
2.2304	3.0123	50
2.1928	2.9626	51
2.1492	2.9453	52
2.1062	2.9063	53
2.0650	2.8974	54
2.0331	2.8556	55
1.9951	2.8444	56
1.9559	2.7950	57
1.9095	2.7815	58
1.8837	2.7437	59
1.8460	2.7277	60
1.8221	2.6958	61
1.7798	2.6683	62
1.7431	2.6418	63
1.7242	2.6274	64

Framework versions

Transformers 4.33.2
TensorFlow 2.13.0
Datasets 2.14.5
Tokenizers 0.13.3