765dad5674
Model: W-61/llama-3-8b-base-new-dpo-hh-harmless-s_star0.6-4xh200-batch-64-20260421-213851 Source: Original Platform
82 lines
3.3 KiB
Markdown
82 lines
3.3 KiB
Markdown
---
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library_name: transformers
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base_model: W-61/llama-3-8b-base-sft-hh-harmless-4xh200
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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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- Anthropic/hh-rlhf
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model-index:
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- name: llama-3-8b-base-new-dpo-hh-harmless-s_star0.6-4xh200-batch-64-20260421-213851
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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-new-dpo-hh-harmless-s_star0.6-4xh200-batch-64-20260421-213851
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This model is a fine-tuned version of [W-61/llama-3-8b-base-sft-hh-harmless-4xh200](https://huggingface.co/W-61/llama-3-8b-base-sft-hh-harmless-4xh200) on the Anthropic/hh-rlhf dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5427
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- Fcm Dpo/beta: 0.0127
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- Fcm Dpo/q T: 0.3797
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- Fcm Dpo/delta: -0.0085
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- Fcm Dpo/margin: 46.9651
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- Margin Dpo/margin Mean: 46.9651
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- Margin Dpo/margin Std: 76.4295
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- Logps/chosen: -176.9747
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- Logps/rejected: -228.6294
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- Logps/ref Chosen: -74.8595
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- Logps/ref Rejected: -79.5490
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- Logits/chosen: 0.6471
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- Logits/rejected: 0.5976
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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: 2
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- total_train_batch_size: 64
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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 | Fcm Dpo/beta | Fcm Dpo/q T | Fcm Dpo/delta | Fcm Dpo/margin | Margin Dpo/margin Mean | Margin Dpo/margin Std | Logps/chosen | Logps/rejected | Logps/ref Chosen | Logps/ref Rejected | Logits/chosen | Logits/rejected |
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|:-------------:|:------:|:----:|:---------------:|:------------:|:-----------:|:-------------:|:--------------:|:----------------------:|:---------------------:|:------------:|:--------------:|:----------------:|:------------------:|:-------------:|:---------------:|
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| 1.0309 | 0.3023 | 200 | 0.5479 | 0.0706 | 0.3810 | -0.0076 | 8.4404 | 8.4404 | 14.1426 | -88.2471 | -101.3770 | -74.8595 | -79.5490 | 0.3430 | 0.2953 |
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| 1.058 | 0.6047 | 400 | 0.5442 | 0.0156 | 0.3824 | 0.0052 | 37.3081 | 37.3081 | 61.1427 | -151.6879 | -193.6855 | -74.8595 | -79.5490 | 0.6412 | 0.5884 |
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| 1.1526 | 0.9070 | 600 | 0.5427 | 0.0127 | 0.3797 | -0.0085 | 46.9651 | 46.9651 | 76.4295 | -176.9747 | -228.6294 | -74.8595 | -79.5490 | 0.6471 | 0.5976 |
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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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