QA_using_DistilBERT_LORA_qv

haurajahra/QA_using_DistilBERT_LORA_qv

QA_using_DistilBERT_LORA_qv is a machine learning model from haurajahra. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

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Public

Updated Nov 28, 2023

Repo size

165 MB

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Public

Hugging Face

Repo makeup

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At a glance

License: apache-2.0
Access: Public
Created: Nov 27, 2023
Updated: Nov 28, 2023
SHA: 0bae787c

Base models

Model card

From the Hugging Face model README

QA_using_DistilBERT_LORA_qv

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

Loss: 2.7782

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: 0.0001
train_batch_size: 4
eval_batch_size: 64
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss
4.7211	0.01	500	4.4152
4.3014	0.03	1000	4.3057
4.2235	0.04	1500	4.2254
4.1424	0.06	2000	4.1592
4.1312	0.07	2500	4.1091
4.033	0.09	3000	3.8720
3.739	0.1	3500	3.7028
3.6547	0.12	4000	3.5784
3.4915	0.13	4500	3.4967
3.5266	0.15	5000	3.4501
3.4602	0.16	5500	3.5048
3.4749	0.18	6000	3.3635
3.4088	0.19	6500	3.3465
3.3869	0.21	7000	3.3438
3.3835	0.22	7500	3.2838
3.2902	0.23	8000	3.3156
3.2747	0.25	8500	3.2770
3.2968	0.26	9000	3.2578
3.2305	0.28	9500	3.2645
3.2288	0.29	10000	3.1857
3.2717	0.31	10500	3.2326
3.1697	0.32	11000	3.2098
3.1786	0.34	11500	3.2656
3.2063	0.35	12000	3.1725
3.186	0.37	12500	3.1901
3.1389	0.38	13000	3.1706
3.234	0.4	13500	3.1553
3.1207	0.41	14000	3.1764
3.1764	0.42	14500	3.1441
3.1458	0.44	15000	3.1459
3.0631	0.45	15500	3.1461
3.1193	0.47	16000	3.1306
3.0437	0.48	16500	3.1775
3.1309	0.5	17000	3.0853
3.0448	0.51	17500	3.1136
3.0273	0.53	18000	3.0640
3.0826	0.54	18500	3.0786
3.0044	0.56	19000	3.0843
3.0672	0.57	19500	3.0516
3.0447	0.59	20000	3.0581
3.0168	0.6	20500	3.0369
2.9619	0.62	21000	3.0725
3.0981	0.63	21500	3.0389
3.0247	0.64	22000	3.0339
3.041	0.66	22500	3.0465
3.0286	0.67	23000	3.0806
3.0136	0.69	23500	3.0149
2.9814	0.7	24000	3.0128
3.0359	0.72	24500	3.0086
2.9939	0.73	25000	3.0216
2.996	0.75	25500	3.1415
2.9554	0.76	26000	3.0490
2.9773	0.78	26500	3.0457
2.9625	0.79	27000	2.9663
2.9184	0.81	27500	2.9981
2.9735	0.82	28000	3.0404
2.9567	0.84	28500	2.9621
2.9706	0.85	29000	3.0024
2.9436	0.86	29500	2.9535
2.9069	0.88	30000	2.9993
2.9652	0.89	30500	2.9393
2.9426	0.91	31000	2.9693
2.8936	0.92	31500	2.9111
2.9245	0.94	32000	2.9678
2.9054	0.95	32500	2.9263
2.8426	0.97	33000	2.9429
2.8782	0.98	33500	2.9232
2.8963	1.0	34000	2.9545
2.8757	1.01	34500	2.9181
2.853	1.03	35000	2.8925
2.8758	1.04	35500	2.9464
2.9179	1.06	36000	2.9076
2.8924	1.07	36500	2.8874
2.9488	1.08	37000	2.9284
2.8746	1.1	37500	2.9012
2.8026	1.11	38000	2.8679
2.8177	1.13	38500	2.9000
2.8113	1.14	39000	2.9069
2.8047	1.16	39500	2.8755
2.8437	1.17	40000	2.9043
2.8093	1.19	40500	2.8915
2.7881	1.2	41000	2.8665
2.8251	1.22	41500	2.8516
2.8356	1.23	42000	2.8927
2.7805	1.25	42500	2.8759
2.8944	1.26	43000	2.8491
2.88	1.27	43500	2.8458
2.8109	1.29	44000	2.8613
2.7595	1.3	44500	2.8734
2.8038	1.32	45000	2.8344
2.8113	1.33	45500	2.8448
2.8396	1.35	46000	2.8216
2.833	1.36	46500	2.8445
2.7711	1.38	47000	2.8499
2.7933	1.39	47500	2.8649
2.8079	1.41	48000	2.8390
2.781	1.42	48500	2.7999
2.8195	1.44	49000	2.8320
2.7553	1.45	49500	2.8500
2.7769	1.47	50000	2.8364
2.6745	1.48	50500	2.8392
2.7891	1.49	51000	2.8166
2.7691	1.51	51500	2.8195
2.7744	1.52	52000	2.8505
2.739	1.54	52500	2.8055
2.7843	1.55	53000	2.8633
2.7072	1.57	53500	2.8214
2.7658	1.58	54000	2.8178
2.7271	1.6	54500	2.8075
2.8387	1.61	55000	2.8025
2.7425	1.63	55500	2.8061
2.7464	1.64	56000	2.7882
2.7442	1.66	56500	2.8161
2.7398	1.67	57000	2.8091
2.7081	1.69	57500	2.8166
2.759	1.7	58000	2.8014
2.6873	1.71	58500	2.7949
2.8057	1.73	59000	2.8044
2.8156	1.74	59500	2.7860
2.6884	1.76	60000	2.7931
2.7627	1.77	60500	2.7931
2.6991	1.79	61000	2.7895
2.8059	1.8	61500	2.7981
2.7018	1.82	62000	2.7972
2.7027	1.83	62500	2.7956
2.7658	1.85	63000	2.7949
2.7735	1.86	63500	2.7803
2.6972	1.88	64000	2.7894
2.6512	1.89	64500	2.8087
2.6856	1.9	65000	2.7795
2.7292	1.92	65500	2.7772
2.7744	1.93	66000	2.7821
2.8022	1.95	66500	2.7858
2.7054	1.96	67000	2.7816
2.7255	1.98	67500	2.7740
2.6243	1.99	68000	2.7782

Framework versions

Transformers 4.35.2
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0

License: apache-2.0
Created: Nov 27, 2023
Updated: Nov 28, 2023