bert-base-uncased-classification-seq2seq

irfanamal/bert-base-uncased-classification-seq2seq

bert-base-uncased-classification-seq2seq is a machine learning model from irfanamal. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers.

should probably proofread and complete it, then remove this comment. --

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At a glance

Library: transformers
Model type: encoder-decoder
Access: Public
Created: Jun 14, 2023
Updated: Jun 15, 2023
SHA: 0411d9d1

Model card

From the Hugging Face model README

bert-base-uncased-classification-seq2seq

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

Loss: 14.625
Accuracy: 0.1667

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: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.0056	1.0	2500	12.4694	0.1667
0.0015	2.0	5000	13.2865	0.1667
0.0006	3.0	7500	13.8803	0.1667
0.0003	4.0	10000	14.3258	0.1667
0.0002	5.0	12500	14.625	0.1667

Framework versions

Transformers 4.29.2
Pytorch 2.0.0
Datasets 2.1.0
Tokenizers 0.13.3

Library: transformers
Type: encoder-decoder
Created: Jun 14, 2023
Updated: Jun 15, 2023