gpt2-rm-tldr

XanderJC/gpt2-rm-tldr

gpt2-rm-tldr is a text classification model from XanderJC. 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: gpt2
Access: Public
Created: Jan 20, 2024
Updated: Jan 20, 2024
SHA: 781b5e59

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Base models

Model card

From the Hugging Face model README

gpt2-rm-tldr

This model is a fine-tuned version of gpt2 on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.0106
Accuracy: 0.5547

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: 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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.6765	1.0	2626	0.6814	0.5654
0.6797	2.0	5252	0.6723	0.5821
0.6248	3.0	7878	0.6872	0.5774
0.5794	4.0	10504	0.7225	0.5658
0.4361	5.0	13130	0.7765	0.5583
0.4558	6.0	15756	0.7988	0.5635
0.5247	7.0	18382	0.8247	0.5581
0.4311	8.0	21008	0.8917	0.5545
0.426	9.0	23634	0.9631	0.5527
0.3895	10.0	26260	1.0106	0.5547

Framework versions

Transformers 4.36.2
Pytorch 2.1.2+cu121
Datasets 2.15.0
Tokenizers 0.15.0

Task: Text Classification
Library: transformers
Type: gpt2
License: mit
Created: Jan 20, 2024
Updated: Jan 20, 2024