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README.md ADDED
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+ ---
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+ base_model: unsloth/qwen2-7b-bnb-4bit
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+ library_name: peft
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+ license: apache-2.0
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+ tags:
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+ - unsloth
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+ - generated_from_trainer
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+ model-index:
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+ - name: Qwen2-7B_magiccoder_reverse
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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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+ # Qwen2-7B_magiccoder_reverse
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+
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+ This model is a fine-tuned version of [unsloth/qwen2-7b-bnb-4bit](https://huggingface.co/unsloth/qwen2-7b-bnb-4bit) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.0907
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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: 0.0003
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+ - train_batch_size: 8
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+ - eval_batch_size: 8
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+ - seed: 42
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+ - gradient_accumulation_steps: 8
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+ - total_train_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: 0.02
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+ - num_epochs: 1
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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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+ | 0.9111 | 0.0261 | 4 | 0.9716 |
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+ | 1.0695 | 0.0522 | 8 | 1.1827 |
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+ | 1.1409 | 0.0783 | 12 | 1.1378 |
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+ | 1.1017 | 0.1044 | 16 | 1.1270 |
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+ | 1.1579 | 0.1305 | 20 | 1.1441 |
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+ | 1.0234 | 0.1566 | 24 | 1.1212 |
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+ | 1.0225 | 0.1827 | 28 | 1.1567 |
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+ | 1.1587 | 0.2088 | 32 | 1.1425 |
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+ | 1.0519 | 0.2349 | 36 | 1.1214 |
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+ | 1.1006 | 0.2610 | 40 | 1.1195 |
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+ | 1.1443 | 0.2871 | 44 | 1.1159 |
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+ | 1.1088 | 0.3132 | 48 | 1.1123 |
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+ | 1.0303 | 0.3393 | 52 | 1.1125 |
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+ | 1.0499 | 0.3654 | 56 | 1.1232 |
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+ | 1.082 | 0.3915 | 60 | 1.1239 |
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+ | 1.1319 | 0.4176 | 64 | 1.1299 |
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+ | 1.1228 | 0.4437 | 68 | 1.1170 |
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+ | 1.0796 | 0.4698 | 72 | 1.1129 |
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+ | 1.0974 | 0.4959 | 76 | 1.1162 |
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+ | 1.0566 | 0.5220 | 80 | 1.1066 |
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+ | 1.1243 | 0.5481 | 84 | 1.1036 |
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+ | 1.0449 | 0.5742 | 88 | 1.1075 |
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+ | 1.1215 | 0.6003 | 92 | 1.1022 |
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+ | 1.0506 | 0.6264 | 96 | 1.0941 |
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+ | 1.1367 | 0.6525 | 100 | 1.0924 |
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+ | 1.03 | 0.6786 | 104 | 1.1014 |
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+ | 1.0844 | 0.7047 | 108 | 1.1160 |
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+ | 1.0575 | 0.7308 | 112 | 1.1058 |
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+ | 1.0169 | 0.7569 | 116 | 1.1061 |
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+ | 1.002 | 0.7830 | 120 | 1.1091 |
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+ | 1.0741 | 0.8091 | 124 | 1.1094 |
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+ | 1.0651 | 0.8352 | 128 | 1.1032 |
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+ | 1.1222 | 0.8613 | 132 | 1.0976 |
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+ | 1.0595 | 0.8874 | 136 | 1.0952 |
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+ | 1.0879 | 0.9135 | 140 | 1.0931 |
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+ | 1.0433 | 0.9396 | 144 | 1.0917 |
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+ | 1.1012 | 0.9657 | 148 | 1.0908 |
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+ | 1.0587 | 0.9918 | 152 | 1.0907 |
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+
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+
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+ ### Framework versions
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+
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+ - PEFT 0.12.0
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+ - Transformers 4.44.0
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+ - Pytorch 2.4.0+cu121
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+ - Datasets 2.20.0
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+ - Tokenizers 0.19.1
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