---
base_model: gpt2
tags:
- generated_from_trainer
model-index:
- name: basho_haiku_gpt2_test
  results: []
---

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# basho_haiku_gpt2_test

Generate a Haiku in the style of Matsuo Bashō given an initial word prompt!

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on a Haiku dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7002

### Training hyperparameters

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

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.9095        | 0.11  | 100  | 0.6605          |
| 0.6638        | 0.22  | 200  | 0.6303          |
| 0.6456        | 0.33  | 300  | 0.6163          |
| 0.6421        | 0.45  | 400  | 0.6139          |
| 0.6421        | 0.56  | 500  | 0.6069          |
| 0.6182        | 0.67  | 600  | 0.5944          |
| 0.6277        | 0.78  | 700  | 0.5910          |
| 0.6409        | 0.89  | 800  | 0.5878          |
| 0.6047        | 1.0   | 900  | 0.5807          |
| 0.4944        | 1.11  | 1000 | 0.5847          |
| 0.4878        | 1.23  | 1100 | 0.5897          |
| 0.4706        | 1.34  | 1200 | 0.5947          |
| 0.4829        | 1.45  | 1300 | 0.5866          |
| 0.4742        | 1.56  | 1400 | 0.5875          |
| 0.4555        | 1.67  | 1500 | 0.5884          |
| 0.4713        | 1.78  | 1600 | 0.5890          |
| 0.4669        | 1.9   | 1700 | 0.5848          |
| 0.475         | 2.01  | 1800 | 0.5838          |
| 0.3762        | 2.12  | 1900 | 0.6123          |
| 0.3703        | 2.23  | 2000 | 0.6172          |
| 0.3772        | 2.34  | 2100 | 0.6118          |
| 0.3731        | 2.45  | 2200 | 0.6090          |
| 0.3662        | 2.56  | 2300 | 0.6151          |
| 0.3894        | 2.68  | 2400 | 0.6132          |
| 0.3663        | 2.79  | 2500 | 0.6195          |
| 0.368         | 2.9   | 2600 | 0.6163          |
| 0.3735        | 3.01  | 2700 | 0.6191          |
| 0.3006        | 3.12  | 2800 | 0.6518          |
| 0.3071        | 3.23  | 2900 | 0.6603          |
| 0.2898        | 3.34  | 3000 | 0.6629          |
| 0.2986        | 3.46  | 3100 | 0.6648          |
| 0.3107        | 3.57  | 3200 | 0.6558          |
| 0.3064        | 3.68  | 3300 | 0.6568          |
| 0.3052        | 3.79  | 3400 | 0.6633          |
| 0.3069        | 3.9   | 3500 | 0.6626          |
| 0.2872        | 4.01  | 3600 | 0.6641          |
| 0.2711        | 4.12  | 3700 | 0.6848          |
| 0.2584        | 4.24  | 3800 | 0.6944          |
| 0.2606        | 4.35  | 3900 | 0.7007          |
| 0.2538        | 4.46  | 4000 | 0.7029          |
| 0.2481        | 4.57  | 4100 | 0.7014          |
| 0.2466        | 4.68  | 4200 | 0.7006          |
| 0.25          | 4.79  | 4300 | 0.6990          |
| 0.2568        | 4.91  | 4400 | 0.7002          |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.0.1+cu117
- Datasets 2.18.0
- Tokenizers 0.15.2