|
--- |
|
license: apache-2.0 |
|
tags: |
|
- generated_from_trainer |
|
- text-generation |
|
- opt |
|
- non-commercial |
|
- dialogue |
|
- chatbot |
|
|
|
inference: false |
|
--- |
|
|
|
# pszemraj/opt-peter-2.7B |
|
|
|
This model is a fine-tuned version of [facebook/opt-2.7b](https://huggingface.co./facebook/opt-2.7b) on about 80k whatsapp/text messages (mine). Please use responsibly :) |
|
|
|
Test it out on Google Colab [here](https://colab.research.google.com/gist/pszemraj/26a69775c9d012051396ab5ae980f5c1/example-text-gen-pszemraj-opt-peter-2-7b.ipynb)! |
|
|
|
 |
|
|
|
## Model description |
|
|
|
- Exploring to see how OPT does in terms of dialogue/conversational applications |
|
- Seems to do a lot better than GPT-Neo with similar training parameters |
|
|
|
## Intended uses & limitations |
|
|
|
> The base model has a custom license which propogates to this one. Most importantly, it cannot be used commercially. Read more here: [facebook/opt-2.7b](https://huggingface.co./facebook/opt-2.7b) |
|
|
|
- the model is probably too large to use via API here. Use in Python with GPU RAM / CPU RAM > 12 gb, Colab notebook linked above. |
|
- alternatively, you can message [a bot on telegram](http://t.me/GPTPeter_bot) where I test LLMs for dialogue generation |
|
- **any statements or claims made by this model do not reflect actual claims/statements by me.** Keep in mind it is a _fine-tuned_ version of the model on my data, so things from pre-training are also present in outputs. |
|
|
|
## Training and evaluation data |
|
|
|
More information needed |
|
|
|
## Training procedure |
|
|
|
### Training hyperparameters |
|
|
|
The following hyperparameters were used during training: |
|
- learning_rate: 4e-05 |
|
- train_batch_size: 8 |
|
- eval_batch_size: 8 |
|
- seed: 42 |
|
- distributed_type: multi-GPU |
|
- gradient_accumulation_steps: 16 |
|
- 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: 0.01 |
|
- num_epochs: 3 |
|
|
|
### Training results |
|
|
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.19.2 |
|
- Pytorch 1.10.0+cu113 |
|
- Datasets 2.2.2 |
|
- Tokenizers 0.12.1 |
|
|
