README.md

metadata

license: mit
tags:
  - generated_from_trainer
datasets:
  - Fraser/short-jokes
metrics:
  - accuracy
model-index:
  - name: gpt2-jokes
    results:
      - task:
          name: Causal Language Modeling
          type: text-generation
        dataset:
          name: Fraser/short-jokes
          type: Fraser/short-jokes
          config: default
          split: train[:5%]
          args: default
        metrics:
          - name: Accuracy
            type: accuracy
            value: 0.8760281609284458

gpt2-jokes

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

• Loss: 0.6851
• Accuracy: 0.8760

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: 8
• eval_batch_size: 8
• seed: 42
• distributed_type: multi-GPU
• num_devices: 4
• total_train_batch_size: 32
• total_eval_batch_size: 32
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 1.0

Training results

Framework versions

• Transformers 4.28.0.dev0
• Pytorch 2.0.0-rc1
• Datasets 2.10.1
• Tokenizers 0.13.2