mdeberta-v3-base-finetuned-recores – AI Model by versae | AlphaNeural AI

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mdeberta-v3-base-finetuned-recores

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mdeberta-v3-base-finetuned-recores

This model is a fine-tuned version of microsoft/mdeberta-v3-base on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.6094
Accuracy: 0.2011

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: 2e-05
train_batch_size: 1
eval_batch_size: 1
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 3000
num_epochs: 25

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.6112	1.0	1047	1.6094	0.1901
1.608	2.0	2094	1.6094	0.1873
1.6127	3.0	3141	1.6095	0.1983
1.6125	4.0	4188	1.6094	0.2424
1.6118	5.0	5235	1.6094	0.1956
1.6181	6.0	6282	1.6094	0.2094
1.6229	7.0	7329	1.6095	0.1680
1.6125	8.0	8376	1.6094	0.1736
1.6134	9.0	9423	1.6094	0.2066
1.6174	10.0	10470	1.6093	0.2204
1.6161	11.0	11517	1.6096	0.2121
1.6198	12.0	12564	1.6094	0.2039
1.6182	13.0	13611	1.6094	0.2287
1.6208	14.0	14658	1.6094	0.2287
1.6436	15.0	15705	1.6092	0.2287
1.6209	16.0	16752	1.6094	0.2094
1.6097	17.0	17799	1.6094	0.2094
1.6115	18.0	18846	1.6094	0.2149
1.6249	19.0	19893	1.6094	0.1956
1.6201	20.0	20940	1.6094	0.1763
1.6217	21.0	21987	1.6094	0.1956
1.6193	22.0	23034	1.6094	0.1846
1.6171	23.0	24081	1.6095	0.1983
1.6123	24.0	25128	1.6095	0.1846
1.6164	25.0	26175	1.6094	0.2011

Framework versions

Transformers 4.19.0
Pytorch 1.10.1+cu102
Datasets 2.2.1
Tokenizers 0.12.1