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---
license: apache-2.0
tags:
- generated_from_trainer
widget:
- text: "I know you're tired, but can we go for another walk this evening?\nperson beta:\n\n"
example_title: "walk"
- text: "Have you done anything exciting lately?\nperson beta:\n\n"
example_title: "activities"
- text: "hey - do you have a favourite grocery store around here?\nperson beta:\n\n"
example_title: "grocery"
- text: "Can you take me for dinner somewhere nice this time?\nperson beta:\n\n"
example_title: "dinner"
- text: "What's your favorite form of social media?\nperson beta:\n\n"
example_title: "social media"
- text: "Hi, how are you?\nperson beta:\n\n"
example_title: "greeting"
- text: "I am the best; my sister is the worst. What am I?\nperson beta:\n\n"
example_title: "sister"
- text: "What do you call an alligator who's just had surgery to remove his left arm?\nperson beta:\n\n"
example_title: "alligator"
- text: "A man walks into a bar and asks for a drink. The bartender asks for $10, and he pays him $1. What did he pay him with?\nperson beta:\n\n"
example_title: "dollar"
- text: "What did I say was in the mailbox when it was actually in the cabinet?\nperson beta:\n\n"
example_title: "mailbox"
- text: "My friend says that she knows every language, but she doesn't speak any of them.. what's wrong with her?\nperson beta:\n\n"
example_title: "language"
inference:
parameters:
min_length: 2
max_length: 64
length_penalty: 0.7
no_repeat_ngram_size: 2
do_sample: True
top_p: 0.95
top_k: 30
repetition_penalty: 2.1
---
# distilgpt2-tiny-conversational
This model is a fine-tuned version of [distilgpt2](https://huggingface.co/distilgpt2) on a parsed version of Wizard of Wikipedia. Persona alpha/beta framework designed for use with [ai-msgbot](https://github.com/pszemraj/ai-msgbot).
It achieves the following results on the evaluation set:
- Loss: 2.2461
## Model description
- it is a splendid model
## Intended uses & limitations
- [ai-msgbot](https://github.com/pszemraj/ai-msgbot)
## Training and evaluation data
- [wizard of Wikipedia](https://parl.ai/projects/wizard_of_wikipedia/) parsed, from parlAI
## Training procedure
- deepspeed + huggingface trainer, an example notebook is in [ai-msgbot](https://github.com/pszemraj/ai-msgbot)
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 30
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| No log | 1.0 | 418 | 2.7793 |
| 2.9952 | 2.0 | 836 | 2.6914 |
| 2.7684 | 3.0 | 1254 | 2.6348 |
| 2.685 | 4.0 | 1672 | 2.5938 |
| 2.6243 | 5.0 | 2090 | 2.5625 |
| 2.5816 | 6.0 | 2508 | 2.5332 |
| 2.5816 | 7.0 | 2926 | 2.5098 |
| 2.545 | 8.0 | 3344 | 2.4902 |
| 2.5083 | 9.0 | 3762 | 2.4707 |
| 2.4793 | 10.0 | 4180 | 2.4551 |
| 2.4531 | 11.0 | 4598 | 2.4395 |
| 2.4269 | 12.0 | 5016 | 2.4238 |
| 2.4269 | 13.0 | 5434 | 2.4102 |
| 2.4051 | 14.0 | 5852 | 2.3945 |
| 2.3777 | 15.0 | 6270 | 2.3848 |
| 2.3603 | 16.0 | 6688 | 2.3711 |
| 2.3394 | 17.0 | 7106 | 2.3613 |
| 2.3206 | 18.0 | 7524 | 2.3516 |
| 2.3206 | 19.0 | 7942 | 2.3398 |
| 2.3026 | 20.0 | 8360 | 2.3301 |
| 2.2823 | 21.0 | 8778 | 2.3203 |
| 2.2669 | 22.0 | 9196 | 2.3105 |
| 2.2493 | 23.0 | 9614 | 2.3027 |
| 2.2334 | 24.0 | 10032 | 2.2930 |
| 2.2334 | 25.0 | 10450 | 2.2852 |
| 2.2194 | 26.0 | 10868 | 2.2754 |
| 2.2014 | 27.0 | 11286 | 2.2695 |
| 2.1868 | 28.0 | 11704 | 2.2598 |
| 2.171 | 29.0 | 12122 | 2.2539 |
| 2.1597 | 30.0 | 12540 | 2.2461 |
### Framework versions
- Transformers 4.16.1
- Pytorch 1.10.0+cu111
- Tokenizers 0.11.0
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