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--- |
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library_name: transformers |
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license: gemma |
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base_model: google/gemma-2-9b-it |
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tags: |
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- alignment-handbook |
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- trl |
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- simpo |
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- generated_from_trainer |
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- trl |
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- simpo |
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- generated_from_trainer |
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datasets: |
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- princeton-nlp/gemma2-ultrafeedback-armorm |
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model-index: |
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- name: simpo |
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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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# simpo |
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This model is a fine-tuned version of [google/gemma-2-9b-it](https://huggingface.co/google/gemma-2-9b-it) on the princeton-nlp/gemma2-ultrafeedback-armorm dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.7459 |
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- Rewards/chosen: -18.9664 |
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- Rewards/rejected: -23.9949 |
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- Rewards/accuracies: 0.7725 |
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- Rewards/margins: 5.0285 |
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- Logps/rejected: -2.3995 |
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- Logps/chosen: -1.8966 |
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- Logits/rejected: -14.4878 |
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- Logits/chosen: -14.5537 |
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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: 8e-07 |
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- train_batch_size: 2 |
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- eval_batch_size: 4 |
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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: 16 |
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- total_train_batch_size: 128 |
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- total_eval_batch_size: 16 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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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 | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | |
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|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| |
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| 2.7196 | 0.8594 | 400 | 2.7580 | -18.9526 | -23.9387 | 0.7705 | 4.9861 | -2.3939 | -1.8953 | -14.4321 | -14.5024 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.7.0+cu128 |
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- Datasets 2.18.0 |
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- Tokenizers 0.19.1 |
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