mBart-small-dataset-ii-lim-to-eng-002 – AI Model by bedus-creation | AlphaNeural AI

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bedus-creation/
mBart-small-dataset-ii-lim-to-eng-002

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text2text-generation

generated_from_keras_callback

endpoints_compatible

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bedus-creation/t5-small-dataset-ii-lim-to-eng-002

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

Train Loss: 0.2514
Validation Loss: 0.3001
Epoch: 99

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
1.0068	0.4628	0
0.4954	0.3665	1
0.4239	0.3488	2
0.3989	0.3300	3
0.3810	0.3232	4
0.3678	0.3192	5
0.3601	0.3140	6
0.3523	0.3110	7
0.3461	0.3099	8
0.3426	0.3074	9
0.3385	0.3055	10
0.3347	0.3019	11
0.3316	0.3036	12
0.3284	0.2997	13
0.3253	0.2983	14
0.3230	0.3004	15
0.3204	0.2977	16
0.3191	0.2957	17
0.3161	0.2931	18
0.3150	0.2925	19
0.3131	0.2921	20
0.3114	0.2909	21
0.3088	0.2925	22
0.3081	0.2922	23
0.3071	0.2894	24
0.3057	0.2889	25
0.3030	0.2898	26
0.3032	0.2884	27
0.3018	0.2873	28
0.2995	0.2887	29
0.3000	0.2864	30
0.2986	0.2868	31
0.2981	0.2854	32
0.2965	0.2867	33
0.2953	0.2862	34
0.2959	0.2848	35
0.2941	0.2849	36
0.2933	0.2867	37
0.2925	0.2875	38
0.2905	0.2843	39
0.2911	0.2843	40
0.2897	0.2863	41
0.2888	0.2855	42
0.2875	0.2852	43
0.2884	0.2878	44
0.2868	0.2853	45
0.2855	0.2843	46
0.2846	0.2852	47
0.2844	0.2833	48
0.2834	0.2847	49
0.2831	0.2851	50
0.2818	0.2839	51
0.2821	0.2843	52
0.2798	0.2858	53
0.2801	0.2843	54
0.2798	0.2851	55
0.2785	0.2880	56
0.2790	0.2853	57
0.2775	0.2860	58
0.2776	0.2848	59
0.2766	0.2875	60
0.2758	0.2864	61
0.2753	0.2857	62
0.2741	0.2899	63
0.2731	0.2904	64
0.2728	0.2887	65
0.2728	0.2879	66
0.2714	0.2877	67
0.2715	0.2901	68
0.2704	0.2864	69
0.2705	0.2876	70
0.2694	0.2925	71
0.2683	0.2923	72
0.2668	0.2910	73
0.2676	0.2878	74
0.2666	0.2928	75
0.2656	0.2903	76
0.2649	0.2913	77
0.2642	0.2912	78
0.2643	0.2944	79
0.2636	0.2910	80
0.2631	0.2922	81
0.2625	0.2983	82
0.2617	0.2945	83
0.2609	0.2914	84
0.2609	0.2974	85
0.2594	0.2960	86
0.2597	0.2977	87
0.2589	0.2972	88
0.2583	0.2970	89
0.2562	0.2951	90
0.2565	0.3004	91
0.2556	0.2971	92
0.2555	0.2963	93
0.2541	0.2991	94
0.2548	0.3000	95
0.2540	0.3015	96
0.2527	0.3004	97
0.2528	0.3012	98
0.2514	0.3001	99

Framework versions

Transformers 4.33.2
TensorFlow 2.13.0
Datasets 2.14.5
Tokenizers 0.13.3