---
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
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# pythia-1.4b-deduped-jokes

This model is a fine-tuned version of [EleutherAI/pythia-1.4b-deduped](https://huggingface.co/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