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--- |
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library_name: transformers |
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tags: |
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- trl |
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- dpo |
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- alignment-handbook |
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- generated_from_trainer |
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model-index: |
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- name: OpenELM-1_1B-DPO-full-max-14-reward |
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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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# OpenELM-1_1B-DPO-full-max-14-reward |
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This model was trained from scratch on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.1668 |
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- Rewards/chosen: -3.5938 |
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- Rewards/rejected: -4.0 |
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- Rewards/accuracies: 0.4902 |
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- Rewards/margins: 0.4121 |
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- Logps/rejected: -688.0 |
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- Logps/chosen: -676.0 |
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- Logits/rejected: -16.375 |
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- Logits/chosen: -16.875 |
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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-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 16 |
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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: 64 |
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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_ratio: 0.1 |
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- num_epochs: 3 |
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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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| 0.0562 | 0.1047 | 100 | 0.6971 | -1.2578 | -1.5703 | 0.5762 | 0.3145 | -446.0 | -444.0 | -9.3125 | -9.5625 | |
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| 0.0394 | 0.2094 | 200 | 0.7479 | -0.8516 | -1.0078 | 0.5195 | 0.1572 | -390.0 | -404.0 | -12.3125 | -12.75 | |
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| 0.0487 | 0.3141 | 300 | 0.9195 | -1.9922 | -2.3125 | 0.5176 | 0.3203 | -520.0 | -516.0 | -13.4375 | -13.6875 | |
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| 0.0454 | 0.4188 | 400 | 0.8309 | -1.4453 | -1.6016 | 0.4961 | 0.1543 | -448.0 | -462.0 | -15.625 | -15.75 | |
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| 0.0297 | 0.5236 | 500 | 0.8326 | -3.1094 | -3.375 | 0.5039 | 0.2734 | -628.0 | -628.0 | -15.5 | -15.6875 | |
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| 0.0434 | 0.6283 | 600 | 0.8373 | -1.6953 | -1.875 | 0.4941 | 0.1826 | -476.0 | -488.0 | -15.0 | -15.25 | |
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| 0.0496 | 0.7330 | 700 | 0.9407 | -3.7344 | -3.9688 | 0.5332 | 0.2236 | -684.0 | -692.0 | -9.5625 | -10.3125 | |
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| 0.0289 | 0.8377 | 800 | 1.0108 | -3.1406 | -3.25 | 0.4707 | 0.0991 | -612.0 | -632.0 | -13.0625 | -13.3125 | |
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| 0.0259 | 0.9424 | 900 | 1.0869 | -3.6094 | -3.7812 | 0.4648 | 0.1631 | -668.0 | -680.0 | -15.625 | -15.875 | |
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| 0.005 | 1.0471 | 1000 | 1.0944 | -3.4375 | -3.625 | 0.4570 | 0.1758 | -652.0 | -664.0 | -15.0625 | -15.25 | |
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| 0.0156 | 1.1518 | 1100 | 1.2452 | -4.4062 | -4.5938 | 0.4629 | 0.1973 | -748.0 | -760.0 | -16.5 | -16.625 | |
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| 0.0018 | 1.2565 | 1200 | 1.0496 | -3.7344 | -3.9219 | 0.4844 | 0.1885 | -680.0 | -692.0 | -15.5625 | -15.875 | |
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| 0.0046 | 1.3613 | 1300 | 1.0484 | -3.375 | -3.6094 | 0.4980 | 0.2402 | -648.0 | -656.0 | -14.9375 | -15.25 | |
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| 0.0041 | 1.4660 | 1400 | 0.9980 | -3.5156 | -3.8438 | 0.5137 | 0.3379 | -676.0 | -668.0 | -13.8125 | -14.3125 | |
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| 0.0077 | 1.5707 | 1500 | 1.0434 | -3.1719 | -3.5156 | 0.4902 | 0.3535 | -640.0 | -636.0 | -13.875 | -14.375 | |
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| 0.0016 | 1.6754 | 1600 | 1.0882 | -3.8594 | -4.2812 | 0.4922 | 0.4141 | -716.0 | -704.0 | -12.4375 | -12.9375 | |
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| 0.0042 | 1.7801 | 1700 | 1.0261 | -3.3438 | -3.7656 | 0.4941 | 0.4238 | -664.0 | -652.0 | -15.5 | -15.9375 | |
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| 0.0005 | 1.8848 | 1800 | 1.0536 | -3.2344 | -3.5938 | 0.4961 | 0.3555 | -648.0 | -644.0 | -16.625 | -17.0 | |
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| 0.0083 | 1.9895 | 1900 | 1.1039 | -3.4844 | -3.8125 | 0.4883 | 0.3242 | -672.0 | -668.0 | -16.25 | -16.625 | |
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| 0.0003 | 2.0942 | 2000 | 1.1159 | -3.5156 | -3.8438 | 0.4922 | 0.3301 | -672.0 | -672.0 | -16.125 | -16.625 | |
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| 0.0027 | 2.1990 | 2100 | 1.1535 | -3.5938 | -4.0 | 0.4980 | 0.4043 | -688.0 | -680.0 | -16.125 | -16.625 | |
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| 0.0003 | 2.3037 | 2200 | 1.1505 | -3.5781 | -3.9844 | 0.4902 | 0.4062 | -688.0 | -676.0 | -16.25 | -16.625 | |
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| 0.0006 | 2.4084 | 2300 | 1.1535 | -3.5469 | -3.9531 | 0.4902 | 0.4023 | -684.0 | -672.0 | -16.25 | -16.75 | |
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| 0.0002 | 2.5131 | 2400 | 1.1581 | -3.5781 | -3.9844 | 0.4922 | 0.4082 | -688.0 | -676.0 | -16.25 | -16.625 | |
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| 0.0001 | 2.6178 | 2500 | 1.1609 | -3.5625 | -3.9688 | 0.4961 | 0.4082 | -684.0 | -672.0 | -16.375 | -16.75 | |
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| 0.0008 | 2.7225 | 2600 | 1.1668 | -3.5938 | -4.0 | 0.4922 | 0.4121 | -688.0 | -676.0 | -16.375 | -16.75 | |
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| 0.0002 | 2.8272 | 2700 | 1.1668 | -3.5938 | -4.0 | 0.4902 | 0.4121 | -688.0 | -676.0 | -16.375 | -16.75 | |
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| 0.0003 | 2.9319 | 2800 | 1.1668 | -3.5938 | -4.0 | 0.4902 | 0.4121 | -688.0 | -676.0 | -16.375 | -16.875 | |
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### Framework versions |
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- Transformers 4.45.1 |
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- Pytorch 2.3.0 |
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- Datasets 3.0.1 |
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- Tokenizers 0.20.0 |
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