metadata

license: mit
base_model: gpt2
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - recall
  - precision
model-index:
  - name: gpt2-text-classification-v2
    results: []

gpt2-text-classification-v2

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

Loss: 0.2002
Accuracy: 0.9342
F1: 0.9340
Recall: 0.9314
Precision: 0.9367

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 3e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 3
total_train_batch_size: 96
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	Accuracy	F1	Validation Loss	Precision	Recall
0.327	0.9974	260	0.8973	0.8929	0.2559	0.9333	0.8558
0.241	1.9987	521	0.919	0.9180	0.2039	0.9296	0.9066
0.244	3.0	782	0.9154	0.9192	0.2156	0.8799	0.9621
0.1843	3.9974	1042	0.9299	0.9288	0.1888	0.9427	0.9154
0.1608	4.9987	1303	0.9301	0.9291	0.1855	0.9428	0.9158
0.124	6.0	1564	0.9322	0.9319	0.1826	0.9357	0.9282
0.112	6.9974	1820	0.2099	0.9315	0.9303	0.9138	0.9473
0.0903	7.9987	2081	0.2002	0.9342	0.9340	0.9314	0.9367

Framework versions

Transformers 4.41.0
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1