deberta-finetuned-claimdecomp – AI Model by gavulsim | AlphaNeural AI

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gavulsim/
deberta-finetuned-claimdecomp

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text-classification

generated_from_trainer

microsoft/deberta-base

autotrain_compatible

endpoints_compatible

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deberta-finetuned-claimdecomp

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

Loss: 1.7521
Accuracy: 0.205

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: 5e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
training_steps: 30000

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.7301	50.0	5000	1.7496	0.205
1.7267	100.0	10000	1.7525	0.205
1.7277	150.0	15000	1.7508	0.205
1.7278	200.0	20000	1.7508	0.205
1.7222	250.0	25000	1.7506	0.205
1.725	300.0	30000	1.7521	0.205

Framework versions

Transformers 4.34.1
Pytorch 2.1.0+cu118
Datasets 2.14.6
Tokenizers 0.14.1