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v1_2000_STEPS_5e6_rate_01_beta_DPO

Text Generation
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mistral
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dpo
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  1. README.md +89 -0
  2. config.json +26 -0
  3. final_checkpoint/config.json +26 -0
  4. final_checkpoint/generation_config.json +6 -0
  5. final_checkpoint/model-00001-of-00003.safetensors +3 -0
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  10. model-00001-of-00003.safetensors +3 -0
  11. model-00002-of-00003.safetensors +3 -0
  12. model-00003-of-00003.safetensors +3 -0
  13. model.safetensors.index.json +298 -0
  14. special_tokens_map.json +24 -0
  15. tokenizer.json +0 -0
  16. tokenizer_config.json +43 -0
  17. training_args.bin +3 -0
README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: mistralai/Mistral-7B-Instruct-v0.1
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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: v1_2000_STEPS_5e6_rate_01_beta_DPO
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+ results: []
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+ ---
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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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+
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+ # v1_2000_STEPS_5e6_rate_01_beta_DPO
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+
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+ This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.1](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.1) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.0579
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+ - Rewards/chosen: -6.2250
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+ - Rewards/rejected: -6.0633
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+ - Rewards/accuracies: 0.4000
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+ - Rewards/margins: -0.1616
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+ - Logps/rejected: -77.5130
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+ - Logps/chosen: -77.5026
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+ - Logits/rejected: -4.8045
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+ - Logits/chosen: -4.8043
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 5e-06
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+ - train_batch_size: 2
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+ - eval_batch_size: 1
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 4
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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_steps: 100
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+ - training_steps: 2000
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+
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+ ### Training results
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+
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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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+ | 1.2927 | 0.1 | 100 | 1.2512 | -5.1921 | -5.1652 | 0.4418 | -0.0269 | -68.5312 | -67.1737 | -2.1461 | -2.1461 |
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+ | 1.7128 | 0.2 | 200 | 1.4813 | -7.0324 | -6.9155 | 0.4308 | -0.1169 | -86.0349 | -85.5773 | -3.9413 | -3.9413 |
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+ | 1.5461 | 0.29 | 300 | 1.2731 | -5.4304 | -5.3353 | 0.4330 | -0.0951 | -70.2329 | -69.5573 | -3.1316 | -3.1316 |
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+ | 1.9939 | 0.39 | 400 | 1.2127 | -5.0685 | -4.9672 | 0.4505 | -0.1013 | -66.5519 | -65.9385 | -3.9101 | -3.9101 |
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+ | 1.5849 | 0.49 | 500 | 1.2395 | -5.1346 | -5.0482 | 0.4396 | -0.0864 | -67.3612 | -66.5990 | -3.6011 | -3.6011 |
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+ | 1.0981 | 0.59 | 600 | 1.2043 | -4.9745 | -4.8822 | 0.4440 | -0.0923 | -65.7019 | -64.9985 | -3.7103 | -3.7103 |
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+ | 1.9697 | 0.68 | 700 | 1.2507 | -5.1232 | -5.1033 | 0.4681 | -0.0199 | -67.9127 | -66.4848 | -3.6280 | -3.6281 |
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+ | 0.8747 | 0.78 | 800 | 1.1611 | -4.8863 | -4.7797 | 0.4505 | -0.1065 | -64.6770 | -64.1157 | -4.1453 | -4.1453 |
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+ | 1.004 | 0.88 | 900 | 1.1843 | -5.6291 | -5.5168 | 0.4527 | -0.1123 | -72.0471 | -71.5438 | -4.7506 | -4.7510 |
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+ | 1.1444 | 0.98 | 1000 | 1.2340 | -6.0675 | -6.1117 | 0.4571 | 0.0442 | -77.9961 | -75.9278 | -4.5307 | -4.5307 |
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+ | 0.9495 | 1.07 | 1100 | 1.1048 | -6.4880 | -6.3179 | 0.3956 | -0.1701 | -80.0584 | -80.1334 | -4.5289 | -4.5289 |
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+ | 0.8455 | 1.17 | 1200 | 1.2109 | -8.1849 | -7.8918 | 0.3890 | -0.2931 | -95.7973 | -97.1021 | -5.1408 | -5.1408 |
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+ | 0.7447 | 1.27 | 1300 | 1.2187 | -7.3352 | -7.0426 | 0.3890 | -0.2926 | -87.3051 | -88.6049 | -4.4742 | -4.4743 |
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+ | 1.1554 | 1.37 | 1400 | 1.0728 | -6.1506 | -5.9622 | 0.3956 | -0.1884 | -76.5017 | -76.7589 | -5.0027 | -5.0028 |
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+ | 0.7376 | 1.47 | 1500 | 1.0798 | -6.2916 | -6.1208 | 0.4066 | -0.1707 | -78.0880 | -78.1689 | -4.9008 | -4.9008 |
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+ | 0.7962 | 1.56 | 1600 | 1.0666 | -6.4071 | -6.2400 | 0.4022 | -0.1671 | -79.2797 | -79.3242 | -4.8474 | -4.8473 |
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+ | 0.89 | 1.66 | 1700 | 1.0615 | -6.3087 | -6.1398 | 0.3912 | -0.1690 | -78.2774 | -78.3405 | -4.8210 | -4.8209 |
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+ | 0.902 | 1.76 | 1800 | 1.0582 | -6.2322 | -6.0708 | 0.4022 | -0.1614 | -77.5875 | -77.5753 | -4.7973 | -4.7972 |
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+ | 0.7122 | 1.86 | 1900 | 1.0578 | -6.2254 | -6.0638 | 0.4000 | -0.1616 | -77.5177 | -77.5069 | -4.8049 | -4.8048 |
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+ | 0.9455 | 1.95 | 2000 | 1.0579 | -6.2250 | -6.0633 | 0.4000 | -0.1616 | -77.5130 | -77.5026 | -4.8045 | -4.8043 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.39.1
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+ - Pytorch 2.0.0+cu117
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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