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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
library_name: transformers

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