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Model: W-61/llama-3-8b-base-epsilon-dpo-hh-helpful-8xh200
Source: Original Platform

README.md

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+---
+library_name: transformers
+base_model: W-61/llama-3-8b-base-sft-hh-helpful-8xh200
+tags:
+- alignment-handbook
+- epsilon-dpo
+- generated_from_trainer
+datasets:
+- Anthropic/hh-rlhf
+model-index:
+- name: llama-3-8b-base-epsilon-dpo-hh-helpful-8xh200-20260410-233108
+  results: []
+---
+
+<!-- This model card has been generated automatically according to the information the Trainer had access to. You
+should probably proofread and complete it, then remove this comment. -->
+
+# llama-3-8b-base-epsilon-dpo-hh-helpful-8xh200-20260410-233108
+
+This model is a fine-tuned version of [W-61/llama-3-8b-base-sft-hh-helpful-8xh200](https://huggingface.co/W-61/llama-3-8b-base-sft-hh-helpful-8xh200) on the Anthropic/hh-rlhf dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6443
+- Rewards/chosen: -0.4430
+- Rewards/rejected: -0.5884
+- Rewards/accuracies: 0.6402
+- Rewards/margins: 0.1454
+- Logps/chosen: -208.1799
+- Logps/rejected: -243.5746
+- Logps/ref Chosen: -87.8236
+- Logps/ref Rejected: -82.8189
+- Logits/chosen: -0.8325
+- Logits/rejected: -0.7259
+- Kl/p Epsilon Steps: 0.6150
+- Kl/n Epsilon Steps: 0.3850
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 5e-07
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 8
+- total_train_batch_size: 128
+- total_eval_batch_size: 128
+- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/chosen | Logps/rejected | Logps/ref Chosen | Logps/ref Rejected | Logits/chosen | Logits/rejected | Kl/p Epsilon Steps | Kl/n Epsilon Steps |
+|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:------------:|:--------------:|:----------------:|:------------------:|:-------------:|:---------------:|:------------------:|:------------------:|
+| 0.6236        | 0.2941 | 100  | 0.6636          | -0.3033        | -0.3895          | 0.6124             | 0.0862          | -127.6472    | -134.3018      | -87.8236         | -82.8189           | -1.2261       | -1.1807         | 0.5760             | 0.4236             |
+| 0.5934        | 0.5882 | 200  | 0.6429          | -0.5156        | -0.6820          | 0.6324             | 0.1663          | -182.9084    | -209.3034      | -87.8236         | -82.8189           | -0.9817       | -0.8951         | 0.6037             | 0.3958             |
+| 0.6156        | 0.8824 | 300  | 0.6443          | -0.4430        | -0.5884          | 0.6402             | 0.1454          | -208.1799    | -243.5746      | -87.8236         | -82.8189           | -0.8325       | -0.7259         | 0.6150             | 0.3850             |
+
+
+### Framework versions
+
+- Transformers 4.51.0
+- Pytorch 2.3.1+cu121
+- Datasets 2.21.0
+- Tokenizers 0.21.4