Comments (2)
the reward itself is not differentiable and as such you can't backpropagate it. PPO is one way of estimating a differentiable loss from a non-differentiable reward. working on enc-dec support in #75 :)
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Ah yes, nicely noted. The main differentiable output is the ratio between new log probabilities and initial log probabilities, right? log_probs / old_log_probs
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Related Issues (20)
- Different with online dpo papers HOT 1
- finetuning gemma2-2b with multi-gpu get OOM, how do i only do model sharding and no data parallel(i guess it's going into DDP). HOT 2
- I'm closing this issue because no one has provided any code to reproduce the error. If you think you are facing the same problem, please open another issue (link this one) with a precise description and a code to reproduce the error.
- Negative Entropy in TRL PPOv2Trainer TLDR Example HOT 3
- Clarification of 2 Entropies in PPOv2Trainer Documentation
- `OnPolicyConfig` - Rename or revise `num_sample_generations` HOT 1
- AttributeError: 'PPOv2Trainer' object has no attribute 'deepspeed' HOT 3
- Incorrect Doc String for `SFTConfig` HOT 2
- plz make GPOTrainer! (Generalized Preference Optimization)
- AttributeError: 'PPOv2Trainer' object has no attribute 'deepspeed' HOT 3
- ConstantLengthDataset should shuffle the order of samples before packing HOT 2
- The ppo_trainer.generate() call results in an error. HOT 2
- DPOTrainer failed on training Custom Mixture of Experts model with config output_router_logits=True
- Disable the dropout by default in Online DPO HOT 1
- RLOOTrainer & PPOv2Trainer - Modify Name for W&B Logged Table HOT 3
- PPOv2Trainer & RLOOTrainer - Add Safety Check that `policy` object != `ref_policy` object HOT 2
- Always allow `ref_model=None` HOT 5
- Reward model HOT 4
- [DPOTrainer] Tokenizer calculation fail during Q+A concat HOT 3
- Model does not generate eos when SFTTrainer with setup_chat_format is used HOT 1
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