7ca2df9d3d
Model: W-61/qwen3-8b-base-new-dpo-ultrafeedback-4xh200-batch-128-q_t-0.45-s_star-0.35-20260430-143919 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-0.45-s_star-0.35-20260430-143919
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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-0.45-s_star-0.35-20260430-143919
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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: 0.5890
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- Fcm Dpo/beta: 0.0056
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- Margin Dpo/margin Mean: 51.3408
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- Margin Dpo/margin Std: 80.2587
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- Logps/chosen: -323.1461
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- Logps/rejected: -358.7158
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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: -42.7294
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- Kl/rejected Kl Mean: -94.0702
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- Kl/mean: -68.3998
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- Kl/std: 69.5920
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- Logits/chosen: 1.3840
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- Logits/rejected: 1.4393
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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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| 4.9323 | 0.4188 | 200 | 0.5859 | 0.0124 | 24.4991 | 38.5860 | -285.8270 | -294.5549 | -280.4167 | -264.6455 | -5.4103 | -29.9094 | -17.6598 | 33.7800 | 1.5348 | 1.5657 |
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| 4.617 | 0.8377 | 400 | 0.5890 | 0.0056 | 51.3408 | 80.2587 | -323.1461 | -358.7158 | -280.4167 | -264.6455 | -42.7294 | -94.0702 | -68.3998 | 69.5920 | 1.3840 | 1.4393 |
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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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