savinda99
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queer-bert

Text Classification

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text-embeddings-inference

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queer-bert

This model is a fine-tuned version of google-bert/bert-base-cased on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.3661
Accuracy: 0.8438

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: 2

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.3555	1.0	6240	0.3386	0.8393
0.2497	2.0	12480	0.3661	0.8438

Framework versions

Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.19.0
Tokenizers 0.15.2

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Safetensors

Model size

0.1B params

Tensor type

F32

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google-bert/bert-base-cased

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