distilbert-base-uncased-finetuned-winogrande – AI Model by Sumaia | AlphaNeural AI

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Sumaia/
distilbert-base-uncased-finetuned-winogrande

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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distilbert-base-uncased-finetuned-winogrande

This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.9100
Accuracy: 0.5525

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: 1e-05
train_batch_size: 8
eval_batch_size: 4
seed: 11262
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 4000
num_epochs: 8

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	1156	0.6931	0.5036
No log	2.0	2312	0.6926	0.5067
No log	3.0	3468	0.6929	0.5075
No log	4.0	4624	0.6908	0.5272
0.6934	5.0	5780	0.6982	0.5391
0.6934	6.0	6936	0.7557	0.5312
0.6934	7.0	8092	0.8402	0.5478
0.6934	8.0	9248	0.9100	0.5525

Framework versions

Transformers 4.26.1
Pytorch 1.13.1+cpu
Datasets 2.10.1
Tokenizers 0.13.2