Debertalarg_model_multichoice

VuongQuoc/Debertalarg_model_multichoice

Debertalarg_model_multichoice is a multiple choice model from VuongQuoc. Use it for the multiple choice task on the model card, and read the license before you ship it in a product. It is set up for transformers.

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

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At a glance

Task: multiple choice
Library: transformers
Model type: deberta-v2
Access: Public
Created: Aug 26, 2023
Updated: Aug 29, 2023
SHA: c6029231

Model card

From the Hugging Face model README

Debertalarg_model_multichoice

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

Loss: 0.6374

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: 3e-06
train_batch_size: 2
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.8
num_epochs: 2

Training results

Training Loss	Epoch	Step	Validation Loss
1.1605	0.04	500	0.4608
0.9286	0.08	1000	0.4628
1.0432	0.12	1500	0.4584
0.9711	0.15	2000	0.4621
0.9773	0.19	2500	0.4663
0.8774	0.23	3000	0.4755
0.928	0.27	3500	0.4788
0.7664	0.31	4000	0.5324
0.8086	0.35	4500	0.5547
0.7734	0.39	5000	0.5291
0.6808	0.42	5500	0.6206
0.7154	0.46	6000	0.5475
0.5706	0.5	6500	0.6125
0.5246	0.54	7000	0.6268
0.5604	0.58	7500	0.6162
0.5964	0.62	8000	0.5577
0.5431	0.65	8500	0.6210
0.3767	0.69	9000	0.6689
1.3041	0.73	9500	0.4854
1.1143	0.77	10000	0.4706
1.0349	0.81	10500	0.4753
1.0821	0.85	11000	0.4792
1.1573	0.89	11500	0.4748
1.023	0.92	12000	0.5218
1.0442	0.96	12500	0.4865
1.0542	1.0	13000	0.4822
0.8776	1.04	13500	0.5088
0.8876	1.08	14000	0.5967
0.9596	1.12	14500	0.5348
0.9764	1.16	15000	0.6067
0.9227	1.19	15500	0.5799
1.0766	1.23	16000	0.6245
0.9904	1.27	16500	0.6092
0.9606	1.31	17000	0.4992
0.9603	1.35	17500	0.5810
0.9904	1.39	18000	0.5620
1.0295	1.43	18500	0.5608
1.0057	1.46	19000	0.5252
1.0016	1.5	19500	0.5896
0.9924	1.54	20000	0.5939
0.9913	1.58	20500	0.5290
0.9345	1.62	21000	0.6177
1.0221	1.66	21500	0.6169
0.9862	1.7	22000	0.7013
0.9735	1.73	22500	0.6552
0.9601	1.77	23000	0.6497
0.923	1.81	23500	0.6733
0.9139	1.85	24000	0.7223
0.9713	1.89	24500	0.6593
1.015	1.93	25000	0.6622
1.0154	1.96	25500	0.6374

Framework versions

Transformers 4.30.2
Pytorch 2.0.0
Datasets 2.1.0
Tokenizers 0.13.3

Task: multiple choice
Library: transformers
Type: deberta-v2
Created: Aug 26, 2023
Updated: Aug 29, 2023