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allstax/
20231216-045106

Name: 20231216-045106
Availability: InStock

peft

safetensors

generated_from_trainer

apache-2.0

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20231216-045106

This model is a fine-tuned version of AIDC-ai-business/Marcoroni-7B-v3 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.2843

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:

learning_rate: 2.5e-05
train_batch_size: 2
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 2
training_steps: 100
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
2.2541	0.02	1	2.1106
1.5517	0.03	2	2.1106
2.347	0.05	3	2.0350
2.006	0.06	4	1.9297
1.8398	0.08	5	1.8406
1.8506	0.09	6	1.8406
1.8804	0.11	7	1.7621
1.9034	0.12	8	1.6988
0.9835	0.14	9	1.6494
1.4725	0.15	10	1.5915
1.1824	0.17	11	1.5557
1.3356	0.18	12	1.5557
1.1077	0.2	13	1.5242
1.4959	0.22	14	1.4908
1.4881	0.23	15	1.4550
1.2674	0.25	16	1.4201
1.2133	0.26	17	1.3872
1.5423	0.28	18	1.3521
0.9551	0.29	19	1.3212
1.1868	0.31	20	1.2881
1.4799	0.32	21	1.2526
1.2903	0.34	22	1.2154
1.3357	0.35	23	1.1770
0.868	0.37	24	1.1383
1.1978	0.38	25	1.0982
1.2102	0.4	26	1.0575
0.8946	0.42	27	1.0575
1.0671	0.43	28	1.0151
1.0761	0.45	29	0.9715
0.9568	0.46	30	0.9263
0.8203	0.48	31	0.8848
0.8601	0.49	32	0.8408
0.8253	0.51	33	0.7945
0.8098	0.52	34	0.7504
0.6567	0.54	35	0.7110
0.6545	0.55	36	0.6695
0.6036	0.57	37	0.6338
0.6746	0.58	38	0.6018
0.5376	0.6	39	0.5731
0.5674	0.62	40	0.5471
0.4762	0.63	41	0.5218
0.4755	0.65	42	0.4965
0.3974	0.66	43	0.4756
0.8437	0.68	44	0.4607
0.4766	0.69	45	0.4485
0.5403	0.71	46	0.4369
0.4201	0.72	47	0.4244
0.4326	0.74	48	0.4115
0.4669	0.75	49	0.3978
0.5259	0.77	50	0.3867
0.3906	0.78	51	0.3782
0.369	0.8	52	0.3724
0.3314	0.82	53	0.3658
0.4164	0.83	54	0.3585
0.3339	0.85	55	0.3499
0.315	0.86	56	0.3405
0.5404	0.88	57	0.3340
0.3136	0.89	58	0.3302
0.3574	0.91	59	0.3275
0.3466	0.92	60	0.3249
0.3097	0.94	61	0.3226
0.4212	0.95	62	0.3208
0.3183	0.97	63	0.3184
0.2762	0.98	64	0.3162
0.3936	1.0	65	0.3143
0.303	1.02	66	0.3128
0.3813	1.03	67	0.3108
0.3065	1.05	68	0.3089
0.2457	1.06	69	0.3069
0.4008	1.08	70	0.3053
0.3131	1.09	71	0.3040
0.2483	1.11	72	0.3027
0.2445	1.12	73	0.3016
0.2717	1.14	74	0.3003
0.6308	1.15	75	0.2991
0.3271	1.17	76	0.2980
0.3013	1.18	77	0.2971
0.2951	1.2	78	0.2960
0.2514	1.22	79	0.2950
0.2836	1.23	80	0.2940
0.2538	1.25	81	0.2929
0.312	1.26	82	0.2921
0.2773	1.28	83	0.2912
0.2957	1.29	84	0.2904
0.3997	1.31	85	0.2896
0.3084	1.32	86	0.2889
0.2521	1.34	87	0.2882
0.2873	1.35	88	0.2877
0.2419	1.37	89	0.2872
0.2691	1.38	90	0.2867
0.6368	1.4	91	0.2864
0.2299	1.42	92	0.2860
0.4967	1.43	93	0.2857
0.2827	1.45	94	0.2855
0.2501	1.46	95	0.2853
0.2285	1.48	96	0.2851
0.269	1.49	97	0.2849
0.2539	1.51	98	0.2847
0.2798	1.52	99	0.2845
0.2695	1.54	100	0.2843

Framework versions

PEFT 0.7.2.dev0
Transformers 4.37.0.dev0
Pytorch 2.1.0+cu121
Datasets 2.15.0
Tokenizers 0.15.0

allstax/20231216-045106

20231216-045106

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

allstax/
20231216-045106