a1e826d8db
Model: jackf857/qwen-3-8b-base-r-dpo-ultrafeedback-4xH200-batch-128-rerun-2-runpod Source: Original Platform
library_name, base_model, tags, datasets, model-index
| library_name | base_model | tags | datasets | model-index | |||||||||
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| transformers | jackf857/qwen3-8b-base-sft-ultrachat-4xh200-batch-128 |
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qwen3-8b-base-r-dpo-ultrafeedback-4xh200-batch-128
This model is a fine-tuned version of jackf857/qwen3-8b-base-sft-ultrachat-4xh200-batch-128 on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:
- Loss: 0.5469
- R Dpo/chosen Len: 294.4800
- R Dpo/rejected Len: 249.8700
- R Dpo/length Delta: 44.6100
- R Dpo/regularization Term: 4.4610
- Logps/chosen: -2936.7747
- Logps/rejected: -2579.1685
- Logps/ref Chosen: -281.4850
- Logps/ref Rejected: -261.8005
- Logits/chosen: 0.6320
- Logits/rejected: 0.5334
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 | R Dpo/chosen Len | R Dpo/rejected Len | R Dpo/length Delta | R Dpo/regularization Term | Logps/chosen | Logps/rejected | Logps/ref Chosen | Logps/ref Rejected | Logits/chosen | Logits/rejected |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 6.6608 | 0.4188 | 200 | 0.7288 | 294.4800 | 249.8700 | 44.6100 | 4.4610 | -2819.1780 | -2438.3210 | -281.4850 | -261.8005 | 0.6077 | 0.5856 |
| 4.5388 | 0.8377 | 400 | 0.5469 | 294.4800 | 249.8700 | 44.6100 | 4.4610 | -2936.7747 | -2579.1685 | -281.4850 | -261.8005 | 0.6320 | 0.5334 |
Framework versions
- Transformers 4.51.0
- Pytorch 2.3.1+cu121
- Datasets 2.21.0
- Tokenizers 0.21.4