Asynchronous RLHF
Collection
Models and datasets for asynchronous rlhf paper, see code at https://github.com/mnoukhov/async_rlhf • 10 items • Updated
How to use mnoukhov/pythia410m-rm-tldr6.9b with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="mnoukhov/pythia410m-rm-tldr6.9b") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("mnoukhov/pythia410m-rm-tldr6.9b")
model = AutoModelForSequenceClassification.from_pretrained("mnoukhov/pythia410m-rm-tldr6.9b")This model is a fine-tuned version of mnoukhov/pythia410m-sft-tldr on an unknown dataset. It achieves the following results on the evaluation set:
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The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5507 | 0.2006 | 291 | 0.5506 | 0.7176 |
| 0.4921 | 0.4011 | 582 | 0.5163 | 0.7394 |
| 0.4727 | 0.6017 | 873 | 0.5194 | 0.7368 |
| 0.439 | 0.8022 | 1164 | 0.5162 | 0.7418 |
Base model
EleutherAI/pythia-410m-deduped