seqcl – AI Model by judithrosell | AlphaNeural AI

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judithrosell/
seqcl

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text-classification

generated_from_trainer

autotrain_compatible

endpoints_compatible

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seqcl

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: 0.8302
Accuracy: 0.6444

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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
No log	1.0	9	0.6533	0.6667
No log	2.0	18	0.7237	0.5333
No log	3.0	27	0.6231	0.7111
No log	4.0	36	0.7202	0.6
No log	5.0	45	0.6903	0.6444
No log	6.0	54	0.7546	0.6222
No log	7.0	63	0.7595	0.6222
No log	8.0	72	0.7999	0.6222
No log	9.0	81	0.8137	0.6444
No log	10.0	90	0.8302	0.6444

Framework versions

Transformers 4.28.1
Pytorch 2.0.0+cu118
Datasets 2.11.0
Tokenizers 0.13.3