---
license: mit
tags:
- generated_from_trainer
datasets:
- generator
model-index:
- name: aochildes-log-rarity-seed
  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. -->

# aochildes-log-rarity-seed

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 4.1414

## 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: 0.0005
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- num_epochs: 6
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 6.3548        | 0.29  | 500   | 5.3339          |
| 5.0444        | 0.59  | 1000  | 4.9261          |
| 4.7132        | 0.88  | 1500  | 4.6909          |
| 4.4499        | 1.17  | 2000  | 4.5531          |
| 4.3078        | 1.47  | 2500  | 4.4357          |
| 4.2045        | 1.76  | 3000  | 4.3447          |
| 4.0812        | 2.05  | 3500  | 4.2654          |
| 3.8961        | 2.35  | 4000  | 4.2330          |
| 3.8785        | 2.64  | 4500  | 4.1725          |
| 3.8431        | 2.93  | 5000  | 4.1244          |
| 3.6353        | 3.23  | 5500  | 4.1232          |
| 3.5952        | 3.52  | 6000  | 4.1008          |
| 3.5747        | 3.81  | 6500  | 4.0651          |
| 3.4761        | 4.11  | 7000  | 4.0742          |
| 3.3222        | 4.4   | 7500  | 4.0703          |
| 3.3167        | 4.69  | 8000  | 4.0574          |
| 3.3126        | 4.99  | 8500  | 4.0452          |
| 3.149         | 5.28  | 9000  | 4.0642          |
| 3.1431        | 5.57  | 9500  | 4.0633          |
| 3.1358        | 5.87  | 10000 | 4.0628          |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.11.0+cu113
- Datasets 2.13.0
- Tokenizers 0.13.3