| | --- |
| | license: apache-2.0 |
| | tags: |
| | - generated_from_trainer |
| | - text-generation |
| | - opt |
| | - non-commercial |
| | - dialogue |
| | - chatbot |
| |
|
| | widget: |
| | - text: "If you could live anywhere, where would it be? peter szemraj:" |
| | example_title: "live anywhere" |
| | - text: "What would you sing at Karaoke night? peter szemraj:" |
| | example_title: "Karaoke" |
| | - text: "If you could hire someone to help you, would it be with cleaning, cooking, or yard work? peter szemraj:" |
| | example_title: "help" |
| | - text: "What form of public transportation do you prefer? (air, boat, train, bus, car, etc.) peter szemraj:" |
| | example_title: "transportation" |
| | - text: "What's your favorite zoo animal? peter szemraj:" |
| | example_title: "animal" |
| | - text: "Do you like or dislike surprises? Why or why not? peter szemraj:" |
| | example_title: "surprises" |
| | - text: "What celebrity would you like to meet at Starbucks for a cup of coffee? peter szemraj:" |
| | example_title: "celebrity " |
| | |
| | inference: |
| | parameters: |
| | min_length: 2 |
| | max_length: 64 |
| | length_penalty: 0.7 |
| | temperature: 0.3 |
| | no_repeat_ngram_size: 2 |
| | top_k: 20 |
| | do_sample: True |
| | repetition_penalty: 4.5 |
| | --- |
| | |
| |
|
| | # pszemraj/opt-peter-1.3B |
| |
|
| | This model is a fine-tuned version of [pszemraj/opt-peter-1.3B-1E](https://huggingface.co/pszemraj/opt-peter-1.3B-1E) on 80k Whatsapp/iMessages (mine). |
| |
|
| | It achieves the following results on the evaluation set, after training for 1 epoch (_on top of the 1E checkpoint linked above_): |
| |
|
| | - eval_loss: 3.4220 |
| | - eval_runtime: 954.9678 |
| | - eval_samples_per_second: 9.114 |
| | - eval_steps_per_second: 2.279 |
| | - epoch: 1.0 |
| | - step: 1235 |
| |
|
| | ## 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 |
| |
|
| | - OPT has a license that does not allow for commercial use, see original for details |
| | - **any statements or claims made by this model do not reflect actual claims/statements by me** |
| |
|
| |
|
| | ## Training procedure |
| |
|
| | ### Training hyperparameters |
| |
|
| | The following hyperparameters were used during training: |
| | - learning_rate: 3e-05 |
| | - train_batch_size: 4 |
| | - eval_batch_size: 4 |
| | - seed: 42 |
| | - distributed_type: multi-GPU |
| | - gradient_accumulation_steps: 16 |
| | - total_train_batch_size: 64 |
| | - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| | - lr_scheduler_type: cosine |
| | - lr_scheduler_warmup_ratio: 0.01 |
| | - num_epochs: 2 |
| | |
| | ### Framework versions |
| | |
| | - Transformers 4.19.2 |
| | - Pytorch 1.11.0+cu113 |
| | - Tokenizers 0.12.1 |
| | |
