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README.md ADDED
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+ ---
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+ library_name: peft
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+ license: other
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+ base_model: deepseek-ai/deepseek-coder-1.3b-base
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: lemexp-task1-min_symbols_template_full-deepseek-coder-1.3b-base-ddp-12lr
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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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+ # lemexp-task1-min_symbols_template_full-deepseek-coder-1.3b-base-ddp-12lr
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+
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+ This model is a fine-tuned version of [deepseek-ai/deepseek-coder-1.3b-base](https://huggingface.co/deepseek-ai/deepseek-coder-1.3b-base) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.1895
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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: 0.0012
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+ - train_batch_size: 2
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+ - eval_batch_size: 2
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+ - seed: 42
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+ - distributed_type: multi-GPU
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+ - num_devices: 8
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+ - total_train_batch_size: 16
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+ - total_eval_batch_size: 16
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - num_epochs: 12
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-------:|:------:|:---------------:|
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+ | 0.387 | 0.2000 | 2907 | 0.3682 |
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+ | 0.3641 | 0.4001 | 5814 | 0.3537 |
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+ | 0.3563 | 0.6001 | 8721 | 0.3494 |
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+ | 0.3467 | 0.8001 | 11628 | 0.3382 |
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+ | 0.3373 | 1.0001 | 14535 | 0.3465 |
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+ | 0.3347 | 1.2002 | 17442 | 0.3315 |
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+ | 0.3396 | 1.4002 | 20349 | 0.3322 |
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+ | 0.3317 | 1.6002 | 23256 | 0.3243 |
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+ | 0.3245 | 1.8002 | 26163 | 0.3237 |
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+ | 0.3219 | 2.0003 | 29070 | 0.3167 |
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+ | 0.3166 | 2.2003 | 31977 | 0.3250 |
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+ | 0.3179 | 2.4003 | 34884 | 0.3165 |
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+ | 0.3142 | 2.6004 | 37791 | 0.3107 |
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+ | 0.3102 | 2.8004 | 40698 | 0.3038 |
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+ | 0.3094 | 3.0004 | 43605 | 0.3081 |
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+ | 0.3039 | 3.2004 | 46512 | 0.2971 |
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+ | 0.3023 | 3.4005 | 49419 | 0.2910 |
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+ | 0.297 | 3.6005 | 52326 | 0.2912 |
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+ | 0.2947 | 3.8005 | 55233 | 0.2958 |
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+ | 0.2925 | 4.0006 | 58140 | 0.2862 |
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+ | 0.2848 | 4.2006 | 61047 | 0.2842 |
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+ | 0.2842 | 4.4006 | 63954 | 0.2797 |
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+ | 0.2815 | 4.6006 | 66861 | 0.2815 |
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+ | 0.2795 | 4.8007 | 69768 | 0.2784 |
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+ | 0.2735 | 5.0007 | 72675 | 0.2715 |
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+ | 0.2685 | 5.2007 | 75582 | 0.2766 |
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+ | 0.2698 | 5.4007 | 78489 | 0.2687 |
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+ | 0.268 | 5.6008 | 81396 | 0.2648 |
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+ | 0.2623 | 5.8008 | 84303 | 0.2647 |
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+ | 0.2613 | 6.0008 | 87210 | 0.2587 |
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+ | 0.2568 | 6.2009 | 90117 | 0.2573 |
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+ | 0.2544 | 6.4009 | 93024 | 0.2553 |
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+ | 0.2519 | 6.6009 | 95931 | 0.2518 |
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+ | 0.2514 | 6.8009 | 98838 | 0.2525 |
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+ | 0.2519 | 7.0010 | 101745 | 0.2512 |
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+ | 0.239 | 7.2010 | 104652 | 0.2441 |
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+ | 0.2407 | 7.4010 | 107559 | 0.2456 |
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+ | 0.2397 | 7.6010 | 110466 | 0.2433 |
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+ | 0.2342 | 7.8011 | 113373 | 0.2364 |
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+ | 0.2329 | 8.0011 | 116280 | 0.2316 |
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+ | 0.2232 | 8.2011 | 119187 | 0.2307 |
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+ | 0.2213 | 8.4012 | 122094 | 0.2294 |
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+ | 0.2223 | 8.6012 | 125001 | 0.2230 |
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+ | 0.2199 | 8.8012 | 127908 | 0.2216 |
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+ | 0.2174 | 9.0012 | 130815 | 0.2211 |
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+ | 0.208 | 9.2013 | 133722 | 0.2193 |
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+ | 0.2089 | 9.4013 | 136629 | 0.2162 |
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+ | 0.2047 | 9.6013 | 139536 | 0.2120 |
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+ | 0.2028 | 9.8013 | 142443 | 0.2098 |
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+ | 0.2005 | 10.0014 | 145350 | 0.2064 |
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+ | 0.1923 | 10.2014 | 148257 | 0.2040 |
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+ | 0.1926 | 10.4014 | 151164 | 0.2023 |
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+ | 0.1887 | 10.6015 | 154071 | 0.2010 |
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+ | 0.1883 | 10.8015 | 156978 | 0.2004 |
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+ | 0.1865 | 11.0015 | 159885 | 0.1963 |
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+ | 0.1769 | 11.2015 | 162792 | 0.1954 |
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+ | 0.1744 | 11.4016 | 165699 | 0.1928 |
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+ | 0.1721 | 11.6016 | 168606 | 0.1914 |
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+ | 0.1711 | 11.8016 | 171513 | 0.1895 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.14.0
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+ - Transformers 4.47.0
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+ - Pytorch 2.5.1+cu124
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+ - Datasets 3.2.0
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+ - Tokenizers 0.21.0
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