marklicata
/

prompt_classifier

Text Classification

Generated from Trainer

text-embeddings-inference

Model card Files Files and versions

prompt_classifier

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: 0.2677

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: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss
No log	1.0	261	0.3994
0.6077	2.0	522	0.3228
0.6077	3.0	783	0.2677

Framework versions

Transformers 4.44.2
Pytorch 2.3.1+cpu
Datasets 2.20.0
Tokenizers 0.19.1

Downloads last month: 3

Safetensors

Model size

67M params

Tensor type

F32

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distilbert/distilbert-base-uncased

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