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--- |
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license: llama3 |
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base_model: tsavage68/Summary_L3_1000steps_1e7rate_SFT2 |
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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: Summary_L3_1000steps_1e5rate_01beta_CSFTDPO |
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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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# Summary_L3_1000steps_1e5rate_01beta_CSFTDPO |
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This model is a fine-tuned version of [tsavage68/Summary_L3_1000steps_1e7rate_SFT2](https://huggingface.co/tsavage68/Summary_L3_1000steps_1e7rate_SFT2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5961 |
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- Rewards/chosen: -0.8715 |
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- Rewards/rejected: -3.9531 |
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- Rewards/accuracies: 0.1400 |
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- Rewards/margins: 3.0816 |
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- Logps/rejected: -54.7948 |
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- Logps/chosen: -18.0977 |
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- Logits/rejected: -1.3576 |
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- Logits/chosen: -1.3527 |
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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: 1e-05 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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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: 1000 |
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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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| 0.5546 | 0.2004 | 50 | 0.5961 | -0.8720 | -3.9451 | 0.1400 | 3.0730 | -54.7146 | -18.1031 | -1.3571 | -1.3522 | |
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| 0.6585 | 0.4008 | 100 | 0.5961 | -0.8712 | -3.9495 | 0.1400 | 3.0783 | -54.7588 | -18.0949 | -1.3575 | -1.3526 | |
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| 0.6238 | 0.6012 | 150 | 0.5961 | -0.8681 | -3.9389 | 0.1400 | 3.0707 | -54.6525 | -18.0641 | -1.3563 | -1.3514 | |
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| 0.6065 | 0.8016 | 200 | 0.5961 | -0.8725 | -3.9499 | 0.1400 | 3.0774 | -54.7626 | -18.1074 | -1.3568 | -1.3519 | |
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| 0.6238 | 1.0020 | 250 | 0.5961 | -0.8717 | -3.9513 | 0.1400 | 3.0796 | -54.7771 | -18.1000 | -1.3576 | -1.3527 | |
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| 0.6238 | 1.2024 | 300 | 0.5961 | -0.8725 | -3.9481 | 0.1400 | 3.0756 | -54.7450 | -18.1078 | -1.3571 | -1.3522 | |
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| 0.6238 | 1.4028 | 350 | 0.5961 | -0.8727 | -3.9498 | 0.1400 | 3.0771 | -54.7614 | -18.1094 | -1.3572 | -1.3523 | |
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| 0.5718 | 1.6032 | 400 | 0.5961 | -0.8724 | -3.9505 | 0.1400 | 3.0781 | -54.7691 | -18.1072 | -1.3573 | -1.3524 | |
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| 0.5892 | 1.8036 | 450 | 0.5961 | -0.8726 | -3.9502 | 0.1400 | 3.0776 | -54.7655 | -18.1083 | -1.3573 | -1.3523 | |
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| 0.5718 | 2.0040 | 500 | 0.5961 | -0.8717 | -3.9446 | 0.1400 | 3.0728 | -54.7095 | -18.1001 | -1.3575 | -1.3526 | |
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| 0.5718 | 2.2044 | 550 | 0.5961 | -0.8733 | -3.9538 | 0.1400 | 3.0805 | -54.8019 | -18.1157 | -1.3569 | -1.3521 | |
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| 0.5545 | 2.4048 | 600 | 0.5961 | -0.8691 | -3.9509 | 0.1400 | 3.0818 | -54.7729 | -18.0740 | -1.3573 | -1.3524 | |
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| 0.5199 | 2.6052 | 650 | 0.5961 | -0.8731 | -3.9531 | 0.1400 | 3.0800 | -54.7946 | -18.1135 | -1.3573 | -1.3524 | |
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| 0.6238 | 2.8056 | 700 | 0.5961 | -0.8719 | -3.9544 | 0.1400 | 3.0826 | -54.8080 | -18.1013 | -1.3581 | -1.3532 | |
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| 0.6065 | 3.0060 | 750 | 0.5961 | -0.8719 | -3.9517 | 0.1400 | 3.0798 | -54.7812 | -18.1017 | -1.3575 | -1.3526 | |
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| 0.6412 | 3.2064 | 800 | 0.5961 | -0.8706 | -3.9530 | 0.1400 | 3.0824 | -54.7941 | -18.0886 | -1.3574 | -1.3525 | |
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| 0.6585 | 3.4068 | 850 | 0.5961 | -0.8715 | -3.9512 | 0.1400 | 3.0798 | -54.7760 | -18.0975 | -1.3577 | -1.3529 | |
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| 0.6238 | 3.6072 | 900 | 0.5961 | -0.8715 | -3.9512 | 0.1400 | 3.0798 | -54.7760 | -18.0975 | -1.3577 | -1.3529 | |
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| 0.5372 | 3.8076 | 950 | 0.5961 | -0.8715 | -3.9531 | 0.1400 | 3.0816 | -54.7948 | -18.0977 | -1.3576 | -1.3527 | |
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| 0.6238 | 4.0080 | 1000 | 0.5961 | -0.8715 | -3.9531 | 0.1400 | 3.0816 | -54.7948 | -18.0977 | -1.3576 | -1.3527 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.0.0+cu117 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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