File size: 2,481 Bytes
5fea7c5 427aff2 7bd53b5 427aff2 49f0b07 427aff2 5fea7c5 2788720 5fea7c5 a31b85b 2788720 5fea7c5 2788720 a31b85b 5fea7c5 a31b85b 5fea7c5 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 |
---
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
|