dfm_ED3

yemen2016/dfm_ED3

dfm_ED3 is a text classification model from yemen2016. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.

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

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At a glance

Task: Text Classification
Library: transformers
License: mit
Model type: bert
Access: Public
Created: Sep 11, 2024
Updated: Sep 11, 2024
SHA: 81eb8c39

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Base models

KennethEnevoldsen/dfm-sentence-encoder-large

Model card

From the Hugging Face model README

dfm_ED3

This model is a fine-tuned version of KennethEnevoldsen/dfm-sentence-encoder-large on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.4093
F1-score: 0.9174

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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	F1-score
No log	1.0	69	0.6188	0.7853
No log	2.0	138	0.5757	0.8835
No log	3.0	207	0.4093	0.9174
No log	4.0	276	0.6598	0.8934
No log	5.0	345	0.7089	0.9096
No log	6.0	414	0.6522	0.9096
No log	7.0	483	0.6856	0.9096
0.1214	8.0	552	0.6935	0.9096
0.1214	9.0	621	0.6891	0.9096
0.1214	10.0	690	0.6906	0.9096

Framework versions

Transformers 4.44.2
Pytorch 2.4.0+cu121
Datasets 2.21.0
Tokenizers 0.19.1

Task: Text Classification
Library: transformers
Type: bert
License: mit
Created: Sep 11, 2024
Updated: Sep 11, 2024