66a4e63baa
Model: W-61/qwen3-8b-base-new-dpo-ultrafeedback-4xh200-batch-128-q_t-0.43-s_star-0.3-20260430-192039 Source: Original Platform
82 lines
3.2 KiB
Markdown
82 lines
3.2 KiB
Markdown
---
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library_name: transformers
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base_model: jackf857/qwen3-8b-base-sft-ultrachat-4xh200-batch-128
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tags:
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- alignment-handbook
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- new-dpo
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- generated_from_trainer
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datasets:
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- HuggingFaceH4/ultrafeedback_binarized
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model-index:
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- name: qwen3-8b-base-new-dpo-ultrafeedback-4xh200-batch-128-q_t-0.43-s_star-0.3-20260430-192039
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# qwen3-8b-base-new-dpo-ultrafeedback-4xh200-batch-128-q_t-0.43-s_star-0.3-20260430-192039
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This model is a fine-tuned version of [jackf857/qwen3-8b-base-sft-ultrachat-4xh200-batch-128](https://huggingface.co/jackf857/qwen3-8b-base-sft-ultrachat-4xh200-batch-128) on the HuggingFaceH4/ultrafeedback_binarized dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.6224
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- Fcm Dpo/beta: 0.0031
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- Margin Dpo/margin Mean: 56.3627
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- Margin Dpo/margin Std: 92.2484
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- Logps/chosen: -335.0146
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- Logps/rejected: -375.6061
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- Logps/ref Chosen: -280.4167
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- Logps/ref Rejected: -264.6455
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- Kl/chosen Kl Mean: -54.5979
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- Kl/rejected Kl Mean: -110.9605
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- Kl/mean: -82.7792
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- Kl/std: 78.7418
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- Logits/chosen: 1.4414
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- Logits/rejected: 1.5117
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-07
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- train_batch_size: 4
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- eval_batch_size: 2
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 4
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- gradient_accumulation_steps: 8
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- total_train_batch_size: 128
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- total_eval_batch_size: 8
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: cosine
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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 1
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Fcm Dpo/beta | Margin Dpo/margin Mean | Margin Dpo/margin Std | Logps/chosen | Logps/rejected | Logps/ref Chosen | Logps/ref Rejected | Kl/chosen Kl Mean | Kl/rejected Kl Mean | Kl/mean | Kl/std | Logits/chosen | Logits/rejected |
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|:-------------:|:------:|:----:|:---------------:|:------------:|:----------------------:|:---------------------:|:------------:|:--------------:|:----------------:|:------------------:|:-----------------:|:-------------------:|:--------:|:-------:|:-------------:|:---------------:|
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| 5.0021 | 0.4188 | 200 | 0.6115 | 0.0077 | 26.9732 | 43.4142 | -286.9713 | -298.1733 | -280.4167 | -264.6455 | -6.5546 | -33.5278 | -20.0412 | 37.3613 | 1.5835 | 1.6292 |
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| 4.8925 | 0.8377 | 400 | 0.6224 | 0.0031 | 56.3627 | 92.2484 | -335.0146 | -375.6061 | -280.4167 | -264.6455 | -54.5979 | -110.9605 | -82.7792 | 78.7418 | 1.4414 | 1.5117 |
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### Framework versions
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- Transformers 4.51.0
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- Pytorch 2.3.1+cu121
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- Datasets 2.21.0
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- Tokenizers 0.21.4
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