---
license: mit
tags:
- generated_from_trainer
datasets:
- generator
model-index:
- name: gpt2-concat-switch-rarity-all-no-cut
  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. -->

# gpt2-concat-switch-rarity-all-no-cut

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: 4.3017

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 6.6978        | 0.29  | 500   | 5.6405          |
| 5.3376        | 0.58  | 1000  | 5.2066          |
| 4.9908        | 0.87  | 1500  | 4.9450          |
| 4.7046        | 1.17  | 2000  | 4.7918          |
| 4.5548        | 1.46  | 2500  | 4.6719          |
| 4.4413        | 1.75  | 3000  | 4.5626          |
| 4.3192        | 2.04  | 3500  | 4.4831          |
| 4.1174        | 2.33  | 4000  | 4.4399          |
| 4.0953        | 2.62  | 4500  | 4.3793          |
| 4.0531        | 2.91  | 5000  | 4.3275          |
| 3.8566        | 3.21  | 5500  | 4.3240          |
| 3.7887        | 3.5   | 6000  | 4.2905          |
| 3.7792        | 3.79  | 6500  | 4.2619          |
| 3.694         | 4.08  | 7000  | 4.2518          |
| 3.5088        | 4.37  | 7500  | 4.2484          |
| 3.5009        | 4.66  | 8000  | 4.2368          |
| 3.49          | 4.95  | 8500  | 4.2237          |
| 3.3364        | 5.24  | 9000  | 4.2358          |
| 3.3147        | 5.54  | 9500  | 4.2337          |
| 3.3098        | 5.83  | 10000 | 4.2329          |


### Framework versions

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