jgeselowitz
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poem_labeler

Text Classification

Generated from Trainer

text-embeddings-inference

Model card Files Files and versions

poem_labeler

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: 1.1318
Accuracy: 0.7315

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
num_epochs: 3.0

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
1.0602	1.0	2382	0.9264	0.6935
0.5889	2.0	4764	0.9186	0.723
0.2638	3.0	7146	1.1318	0.7315

Framework versions

Transformers 4.33.2
Pytorch 2.0.1+cu118
Datasets 2.14.5
Tokenizers 0.13.3

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