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Model: jackf857/qwen3-8b-base-epsilon-dpo-ultrafeedback-4xh200-batch-128
Source: Original Platform

README.md

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+---
+library_name: transformers
+base_model: qwen3-8b-base-sft-ultrachat-4xh200-batch-128-20260420-124036
+tags:
+- alignment-handbook
+- epsilon-dpo
+- generated_from_trainer
+datasets:
+- HuggingFaceH4/ultrafeedback_binarized
+model-index:
+- name: qwen3-8b-base-epsilon-dpo-ultrafeedback-4xh200-batch-128-20260420-124036
+  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. -->
+
+# qwen3-8b-base-epsilon-dpo-ultrafeedback-4xh200-batch-128-20260420-124036
+
+This model is a fine-tuned version of [qwen3-8b-base-sft-ultrachat-4xh200-batch-128-20260420-124036](https://huggingface.co/qwen3-8b-base-sft-ultrachat-4xh200-batch-128-20260420-124036) on the HuggingFaceH4/ultrafeedback_binarized dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6403
+- Epsilon Dpo/beta: 0.0021
+- Epsilon Dpo/loss Margin Mean: 59.0314
+- Epsilon Dpo/beta Margin Mean: 0.1219
+- Epsilon Dpo/beta Margin Std: 0.2152
+- Epsilon Dpo/beta Margin Grad Mean: -0.4699
+- Epsilon Dpo/beta Margin Grad Std: 0.0531
+- Rewards/chosen: -0.1383
+- Rewards/rejected: -0.2601
+- Rewards/accuracies: 0.7165
+- Rewards/margins: 0.1219
+- Logps/chosen: -346.2501
+- Logps/rejected: -389.5577
+- Logps/ref Chosen: -280.4283
+- Logps/ref Rejected: -264.7045
+- Logits/chosen: 1.5736
+- Logits/rejected: 1.9569
+- Kl/p Epsilon Steps: 0.7085
+- Kl/n Epsilon Steps: 0.2855
+
+## 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: 4
+- eval_batch_size: 4
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 4
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 128
+- total_eval_batch_size: 16
+- 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 | Epsilon Dpo/beta | Epsilon Dpo/loss Margin Mean | Epsilon Dpo/beta Margin Mean | Epsilon Dpo/beta Margin Std | Epsilon Dpo/beta Margin Grad Mean | Epsilon Dpo/beta Margin Grad Std | 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 |
+|:-------------:|:------:|:----:|:---------------:|:----------------:|:----------------------------:|:----------------------------:|:---------------------------:|:---------------------------------:|:--------------------------------:|:--------------:|:----------------:|:------------------:|:---------------:|:------------:|:--------------:|:----------------:|:------------------:|:-------------:|:---------------:|:------------------:|:------------------:|
+| 5.0674        | 0.4188 | 200  | 0.6322          | 0.0051           | 28.6770                      | 0.1452                       | 0.2575                      | -0.4644                           | 0.0631                           | -0.0590        | -0.2042          | 0.7170             | 0.1452          | -291.7776    | -304.7309      | -280.4283        | -264.7045          | 1.8063        | 2.1551          | 0.6990             | 0.2930             |
+| 5.1073        | 0.8377 | 400  | 0.6403          | 0.0021           | 59.0314                      | 0.1219                       | 0.2152                      | -0.4699                           | 0.0531                           | -0.1383        | -0.2601          | 0.7165             | 0.1219          | -346.2501    | -389.5577      | -280.4283        | -264.7045          | 1.5736        | 1.9569          | 0.7085             | 0.2855             |
+
+
+### Framework versions
+
+- Transformers 4.51.0
+- Pytorch 2.3.1+cu121
+- Datasets 2.21.0
+- Tokenizers 0.21.4