f172e34488
Model: jackf857/llama-3-8b-base-orpo-ultrafeedback-4xh200-rerun Source: Original Platform
80 lines
2.8 KiB
Markdown
80 lines
2.8 KiB
Markdown
---
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library_name: transformers
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base_model: W-61/llama-3-8b-base-sft-ultrachat-8xh200
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tags:
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- alignment-handbook
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- orpo
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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: llama-3-8b-base-orpo-ultrafeedback-4xh200-rerun
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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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# llama-3-8b-base-orpo-ultrafeedback-4xh200-rerun
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This model is a fine-tuned version of [W-61/llama-3-8b-base-sft-ultrachat-8xh200](https://huggingface.co/W-61/llama-3-8b-base-sft-ultrachat-8xh200) on the HuggingFaceH4/ultrafeedback_binarized dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.2244
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- Rewards/chosen: -0.0088
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- Rewards/rejected: -0.0106
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- Rewards/accuracies: 0.6028
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- Rewards/margins: 0.0018
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- Logps/rejected: -1.0607
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- Logps/chosen: -0.8758
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- Logits/rejected: -0.4873
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- Logits/chosen: -0.5022
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- Nll Loss: 1.2174
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- Log Odds Ratio: -0.6565
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- Log Odds Chosen: 0.2857
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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: 8
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- eval_batch_size: 8
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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: 4
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- total_train_batch_size: 128
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- total_eval_batch_size: 32
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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 | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen | Nll Loss | Log Odds Ratio | Log Odds Chosen |
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|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|:--------:|:--------------:|:---------------:|
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| 5.2395 | 0.4188 | 200 | 1.2644 | -0.0088 | -0.0107 | 0.6008 | 0.0018 | -1.0672 | -0.8826 | -0.4935 | -0.5068 | 1.2561 | -0.6568 | 0.2836 |
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| 4.9046 | 0.8377 | 400 | 1.2244 | -0.0088 | -0.0106 | 0.6028 | 0.0018 | -1.0607 | -0.8758 | -0.4873 | -0.5022 | 1.2174 | -0.6565 | 0.2857 |
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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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