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--- |
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library_name: transformers |
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license: llama3 |
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base_model: tsavage68/IE_L3_1000steps_1e6rate_SFT |
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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: IE_L3_450steps_1e8rate_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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# IE_L3_450steps_1e8rate_01beta_cSFTDPO |
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This model is a fine-tuned version of [tsavage68/IE_L3_1000steps_1e6rate_SFT](https://huggingface.co/tsavage68/IE_L3_1000steps_1e6rate_SFT) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6907 |
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- Rewards/chosen: -0.0040 |
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- Rewards/rejected: -0.0095 |
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- Rewards/accuracies: 0.4050 |
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- Rewards/margins: 0.0055 |
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- Logps/rejected: -75.7223 |
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- Logps/chosen: -82.8379 |
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- Logits/rejected: -0.7979 |
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- Logits/chosen: -0.7409 |
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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-08 |
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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: 450 |
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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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| 0.6965 | 0.4 | 50 | 0.6929 | -0.0030 | -0.0041 | 0.3700 | 0.0011 | -75.6681 | -82.8275 | -0.7963 | -0.7392 | |
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| 0.6948 | 0.8 | 100 | 0.6908 | -0.0022 | -0.0074 | 0.4250 | 0.0052 | -75.7008 | -82.8198 | -0.7961 | -0.7393 | |
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| 0.6904 | 1.2 | 150 | 0.6912 | -0.0066 | -0.0112 | 0.4200 | 0.0046 | -75.7390 | -82.8636 | -0.7971 | -0.7401 | |
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| 0.6902 | 1.6 | 200 | 0.6897 | -0.0027 | -0.0101 | 0.4250 | 0.0074 | -75.7282 | -82.8243 | -0.7964 | -0.7397 | |
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| 0.6858 | 2.0 | 250 | 0.6904 | -0.0049 | -0.0110 | 0.3950 | 0.0061 | -75.7372 | -82.8472 | -0.7971 | -0.7403 | |
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| 0.6903 | 2.4 | 300 | 0.6887 | -0.0076 | -0.0170 | 0.4500 | 0.0094 | -75.7977 | -82.8741 | -0.7971 | -0.7401 | |
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| 0.6859 | 2.8 | 350 | 0.6898 | -0.0058 | -0.0130 | 0.4150 | 0.0072 | -75.7575 | -82.8558 | -0.7979 | -0.7409 | |
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| 0.6978 | 3.2 | 400 | 0.6907 | -0.0040 | -0.0095 | 0.4050 | 0.0055 | -75.7223 | -82.8379 | -0.7979 | -0.7409 | |
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| 0.6889 | 3.6 | 450 | 0.6907 | -0.0040 | -0.0095 | 0.4050 | 0.0055 | -75.7223 | -82.8379 | -0.7979 | -0.7409 | |
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### Framework versions |
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- Transformers 4.44.2 |
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- Pytorch 2.0.0+cu117 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
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