README.md

metadata

license: mit
tags:
  - generated_from_trainer
metrics:
  - f1
  - recall
  - accuracy
model-index:
  - name: GPT2-THESIS
    results: []

GPT2-THESIS

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

• Loss: 0.9762
• F1: 0.7492
• Recall: 0.7492
• Accuracy: 0.7492

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: 32
• eval_batch_size: 32
• 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	Recall	Accuracy
1.1822	1.0	1446	0.9362	0.7065	0.7065	0.7065
0.8791	2.0	2892	0.8616	0.7303	0.7303	0.7303
0.7218	3.0	4338	0.8250	0.7406	0.7406	0.7406
0.6025	4.0	5784	0.8351	0.7509	0.7509	0.7509
0.5142	5.0	7230	0.8781	0.7477	0.7477	0.7477
0.453	6.0	8676	0.8871	0.7526	0.7526	0.7526
0.3813	7.0	10122	0.9216	0.7475	0.7475	0.7475
0.3399	8.0	11568	0.9458	0.7477	0.7477	0.7477
0.3049	9.0	13014	0.9650	0.7504	0.7504	0.7504
0.2861	10.0	14460	0.9762	0.7492	0.7492	0.7492

Framework versions

• Transformers 4.28.0
• Pytorch 2.0.1+cu118
• Datasets 2.14.5
• Tokenizers 0.13.3