metadata

license: mit
base_model: openai-community/gpt2
tags:
  - generated_from_trainer
model-index:
  - name: GPT2-small-finetuned-Maximofn-short-jokes-dataset-casualLM
    results: []
datasets:
  - Maximofn/short-jokes-dataset
language:
  - en
widget:
  - text: <SJ> Why didn't the frog cross the road?
pipeline_tag: text-generation

GPT2-small-finetuned-Maximofn-short-jokes-dataset-casualLM

This model is a fine-tuned version of openai-community/gpt2 on Maximofn/short-jokes-dataset dataset. It achieves the following results on the evaluation set:

It is the result of the post Fine tunning SML

Loss: 3.2013

Model description

This model generated english jokes

Intended uses & limitations

Text generation, english jokes

Training and evaluation data

It is training on Maximofn/short-jokes-dataset dataset.

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 2e-05
train_batch_size: 28
eval_batch_size: 32
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_ratio: 0.1
lr_scheduler_warmup_steps: 100
num_epochs: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss
3.3866	1.0	7447	3.2590
3.2599	2.0	14894	3.1997
3.2126	3.0	22341	3.1920

Framework versions

Transformers 4.42.4
Pytorch 2.3.0+cu121
Datasets 2.20.0
Tokenizers 0.19.1