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metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - Fraser/short-jokes
metrics:
  - accuracy
model-index:
  - name: pythia-1.4b-deduped-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: 0.986989308918276

pythia-1.4b-deduped-jokes

This model is a fine-tuned version of EleutherAI/pythia-1.4b-deduped on the Fraser/short-jokes dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0699
  • Accuracy: 0.9870

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
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 128
  • total_eval_batch_size: 32
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.05
  • training_steps: 400

Training results

Training Loss Epoch Step Validation Loss Accuracy
No log 0.06 100 0.0729 0.9866
No log 0.12 200 0.0716 0.9868
No log 0.17 300 0.0705 0.9869
No log 0.23 400 0.0699 0.9870

Framework versions

  • Transformers 4.29.0.dev0
  • Pytorch 2.0.0-rc1
  • Datasets 2.11.0
  • Tokenizers 0.13.3