Quantization made by Richard Erkhov.

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dadjokes-tuned-opt - AWQ
- Model creator: https://huggingface.co/gnumanth/
- Original model: https://huggingface.co/gnumanth/dadjokes-tuned-opt/




Original model description:
---
license: mit
base_model: facebook/opt-350m
tags:
- trl
- sft
- gnumanth/dadjokes-trained-opt
model-index:
- name: tmp_trainer
  results: []
datasets:
- gnumanth/dad-jokes
language:
- en
pipeline_tag: text-generation
widget:
- text: "joke"
---

<!-- 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. -->

# 

This model is a fine-tuned version of [facebook/opt-350m](https://huggingface.co/facebook/opt-350m) on an [gnumanth/dad-jokes](https://huggingface.co/datasets/gnumanth/dad-jokes) dataset.

## Model description

SFT Trained simple model for fun! 

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

```
TrainOutput(global_step=18, training_loss=2.2378472222222223, metrics={'train_runtime': 149.7511, 'train_samples_per_second': 0.881, 'train_steps_per_second': 0.12, 'total_flos': 9828797644800.0, 'train_loss': 2.2378472222222223, 'epoch': 3.0})
```

### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.1