---
license: mit
tags:
- generated_from_trainer
model-index:
- name: prompt-extend
  results: []
---

<!-- 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. -->

# prompt-extend

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1453

## 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: 0.0001
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 6.3816        | 0.35  | 100  | 4.1823          |
| 3.7123        | 0.69  | 200  | 3.3033          |
| 3.118         | 1.04  | 300  | 2.8311          |
| 2.7291        | 1.39  | 400  | 2.5503          |
| 2.4918        | 1.74  | 500  | 2.3653          |
| 2.3379        | 2.08  | 600  | 2.2375          |
| 2.1952        | 2.43  | 700  | 2.1714          |
| 2.1593        | 2.78  | 800  | 2.1453          |


### Framework versions

- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Datasets 2.6.1
- Tokenizers 0.13.1