#  Reward model based [`deberta-v3-large-tasksource-nli`](https://huggingface.co/sileod/deberta-v3-large-tasksource-nli) fine-tuned on Anthropic/hh-rlhf
For 1 epoch with 1e-5 learning rate.

The data are described in the paper: [Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback](https://arxiv.org/abs/2204.05862). 

Validation accuracy is currently the best publicly available reported: 75.16% (vs 69.25% for `OpenAssistant/reward-model-deberta-v3-large-v2`).
{"language": ["en"], "tags": ["rlhf"], "datasets": ["Anthropic/hh-rlhf"], "model-index": [{"name": "deberta-v3-large-tasksource-rlhf-reward-model", "results": [{"task": {"type": "text-classification", "name": "RLHF"}, "dataset": {"name": "Anthropic/hh-rlhf", "type": "rlhf", "split": "validation"}, "metrics": [{"type": "accuracy", "value": "0,7516", "verified": true}]}]}]}
transformers pytorch deberta-v2 text-classification rlhf en dataset:Anthropic/hh-rlhf arxiv:2204.05862 model-index autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #deberta-v2 #text-classification #rlhf #en #dataset-Anthropic/hh-rlhf #arxiv-2204.05862 #model-index #autotrain_compatible #endpoints_compatible #region-us 

#  Reward model based 'deberta-v3-large-tasksource-nli' fine-tuned on Anthropic/hh-rlhf
For 1 epoch with 1e-5 learning rate.

The data are described in the paper: Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback. 

Validation accuracy is currently the best publicly available reported: 75.16% (vs 69.25% for 'OpenAssistant/reward-model-deberta-v3-large-v2').
#  Reward model based 'deberta-v3-large-tasksource-nli' fine-tuned on Anthropic/hh-rlhf
For 1 epoch with 1e-5 learning rate.

The data are described in the paper: Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback. 

Validation accuracy is currently the best publicly available reported: 75.16% (vs 69.25% for 'OpenAssistant/reward-model-deberta-v3-large-v2').
TAGS
#transformers #pytorch #deberta-v2 #text-classification #rlhf #en #dataset-Anthropic/hh-rlhf #arxiv-2204.05862 #model-index #autotrain_compatible #endpoints_compatible #region-us 
 #  Reward model based 'deberta-v3-large-tasksource-nli' fine-tuned on Anthropic/hh-rlhf
For 1 epoch with 1e-5 learning rate.

The data are described in the paper: Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback. 

Validation accuracy is currently the best publicly available reported: 75.16% (vs 69.25% for 'OpenAssistant/reward-model-deberta-v3-large-v2').
TAGS
#transformers #pytorch #deberta-v2 #text-classification #rlhf #en #dataset-Anthropic/hh-rlhf #arxiv-2204.05862 #model-index #autotrain_compatible #endpoints_compatible #region-us 
#  Reward model based 'deberta-v3-large-tasksource-nli' fine-tuned on Anthropic/hh-rlhf
For 1 epoch with 1e-5 learning rate.

The data are described in the paper: Training a Helpful and Harmless Assistant with Reinforcement Learning from Human Feedback. 

Validation accuracy is currently the best publicly available reported: 75.16% (vs 69.25% for 'OpenAssistant/reward-model-deberta-v3-large-v2').