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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: tsavage68/IE_M2_1000steps_1e7rate_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_M2_350steps_1e8rate_05beta_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_M2_350steps_1e8rate_05beta_cSFTDPO |
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This model is a fine-tuned version of [tsavage68/IE_M2_1000steps_1e7rate_SFT](https://huggingface.co/tsavage68/IE_M2_1000steps_1e7rate_SFT) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6608 |
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- Rewards/chosen: 0.0105 |
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- Rewards/rejected: -0.0599 |
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- Rewards/accuracies: 0.3850 |
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- Rewards/margins: 0.0703 |
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- Logps/rejected: -41.1416 |
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- Logps/chosen: -42.1846 |
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- Logits/rejected: -2.9156 |
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- Logits/chosen: -2.8543 |
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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: 350 |
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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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| 0.6945 | 0.4 | 50 | 0.6933 | 0.0121 | 0.0098 | 0.2450 | 0.0023 | -41.0022 | -42.1813 | -2.9159 | -2.8545 | |
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| 0.6936 | 0.8 | 100 | 0.6888 | 0.0052 | -0.0069 | 0.2150 | 0.0121 | -41.0356 | -42.1952 | -2.9158 | -2.8545 | |
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| 0.6822 | 1.2 | 150 | 0.6646 | 0.0021 | -0.0599 | 0.3650 | 0.0621 | -41.1417 | -42.2012 | -2.9157 | -2.8544 | |
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| 0.6637 | 1.6 | 200 | 0.6652 | 0.0023 | -0.0586 | 0.3600 | 0.0609 | -41.1390 | -42.2010 | -2.9157 | -2.8544 | |
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| 0.6647 | 2.0 | 250 | 0.6601 | 0.0043 | -0.0670 | 0.3900 | 0.0713 | -41.1557 | -42.1968 | -2.9157 | -2.8544 | |
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| 0.6697 | 2.4 | 300 | 0.6624 | 0.0067 | -0.0606 | 0.3800 | 0.0673 | -41.1430 | -42.1922 | -2.9156 | -2.8543 | |
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| 0.6579 | 2.8 | 350 | 0.6608 | 0.0105 | -0.0599 | 0.3850 | 0.0703 | -41.1416 | -42.1846 | -2.9156 | -2.8543 | |
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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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