75 lines
2.1 KiB
Markdown
75 lines
2.1 KiB
Markdown
---
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library_name: transformers
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license: apache-2.0
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base_model: alignment-handbook/zephyr-7b-sft-full
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tags:
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- trl
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- dpo
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- generated_from_trainer
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model-index:
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- name: zephyr-7b-dpo-full
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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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# zephyr-7b-dpo-full
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This model is a fine-tuned version of [alignment-handbook/zephyr-7b-sft-full](https://huggingface.co/alignment-handbook/zephyr-7b-sft-full) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.2016
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- Rewards/chosen: -5.9224
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- Rewards/rejected: -7.8036
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- Rewards/accuracies: 0.7380
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- Rewards/margins: 1.8812
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- Logps/rejected: -3.9018
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- Logps/chosen: -2.9612
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- Logits/rejected: -1.8800
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- Logits/chosen: -1.8679
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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: 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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| 1.2816 | 0.8375 | 400 | 1.2016 | -5.9224 | -7.8036 | 0.7380 | 1.8812 | -3.9018 | -2.9612 | -1.8800 | -1.8679 |
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### Framework versions
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- Transformers 4.45.2
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- Pytorch 2.4.0+cu121
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- Datasets 2.14.6
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- Tokenizers 0.20.1
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