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--- |
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library_name: peft |
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license: other |
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base_model: unsloth/llama-3.2-3b-instruct-bnb-4bit |
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tags: |
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- llama-factory |
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- lora |
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- unsloth |
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- generated_from_trainer |
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model-index: |
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- name: llm3br256-v1.5 |
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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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# llm3br256-v1.5 |
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This model is a fine-tuned version of [meta-llama/Llama-3.2-3B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-3B-Instruct) on the asianpaints dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0157 |
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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: 0.0001 |
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- train_batch_size: 48 |
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- eval_batch_size: 48 |
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- seed: 42 |
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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: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 25 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 0.1302 | 0.1208 | 25 | 0.1429 | |
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| 0.0909 | 0.2415 | 50 | 0.0968 | |
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| 0.062 | 0.3623 | 75 | 0.0748 | |
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| 0.0602 | 0.4831 | 100 | 0.0608 | |
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| 0.057 | 0.6039 | 125 | 0.0552 | |
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| 0.0456 | 0.7246 | 150 | 0.0501 | |
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| 0.0432 | 0.8454 | 175 | 0.0470 | |
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| 0.0416 | 0.9662 | 200 | 0.0447 | |
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| 0.0441 | 1.0870 | 225 | 0.0428 | |
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| 0.0348 | 1.2077 | 250 | 0.0405 | |
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| 0.0355 | 1.3285 | 275 | 0.0386 | |
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| 0.0379 | 1.4493 | 300 | 0.0358 | |
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| 0.032 | 1.5700 | 325 | 0.0354 | |
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| 0.0342 | 1.6908 | 350 | 0.0335 | |
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| 0.0318 | 1.8116 | 375 | 0.0324 | |
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| 0.031 | 1.9324 | 400 | 0.0318 | |
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| 0.0283 | 2.0531 | 425 | 0.0321 | |
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| 0.0275 | 2.1739 | 450 | 0.0337 | |
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| 0.026 | 2.2947 | 475 | 0.0314 | |
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| 0.0244 | 2.4155 | 500 | 0.0285 | |
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| 0.0281 | 2.5362 | 525 | 0.0285 | |
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| 0.0212 | 2.6570 | 550 | 0.0268 | |
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| 0.0221 | 2.7778 | 575 | 0.0267 | |
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| 0.0225 | 2.8986 | 600 | 0.0266 | |
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| 0.0264 | 3.0193 | 625 | 0.0292 | |
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| 0.0196 | 3.1401 | 650 | 0.0280 | |
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| 0.0185 | 3.2609 | 675 | 0.0264 | |
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| 0.0161 | 3.3816 | 700 | 0.0248 | |
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| 0.0186 | 3.5024 | 725 | 0.0226 | |
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| 0.0166 | 3.6232 | 750 | 0.0213 | |
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| 0.0141 | 3.7440 | 775 | 0.0215 | |
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| 0.0186 | 3.8647 | 800 | 0.0211 | |
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| 0.0119 | 3.9855 | 825 | 0.0204 | |
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| 0.0097 | 4.1063 | 850 | 0.0210 | |
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| 0.0095 | 4.2271 | 875 | 0.0204 | |
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| 0.0119 | 4.3478 | 900 | 0.0207 | |
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| 0.0131 | 4.4686 | 925 | 0.0257 | |
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| 0.0123 | 4.5894 | 950 | 0.0228 | |
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| 0.0133 | 4.7101 | 975 | 0.0204 | |
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| 0.0115 | 4.8309 | 1000 | 0.0191 | |
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| 0.0152 | 4.9517 | 1025 | 0.0201 | |
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| 0.0075 | 5.0725 | 1050 | 0.0188 | |
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| 0.0069 | 5.1932 | 1075 | 0.0169 | |
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| 0.0073 | 5.3140 | 1100 | 0.0182 | |
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| 0.0076 | 5.4348 | 1125 | 0.0166 | |
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| 0.0084 | 5.5556 | 1150 | 0.0173 | |
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| 0.0091 | 5.6763 | 1175 | 0.0175 | |
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| 0.0081 | 5.7971 | 1200 | 0.0176 | |
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| 0.0071 | 5.9179 | 1225 | 0.0175 | |
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| 0.0058 | 6.0386 | 1250 | 0.0187 | |
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| 0.0081 | 6.1594 | 1275 | 0.0165 | |
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| 0.0057 | 6.2802 | 1300 | 0.0171 | |
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| 0.0068 | 6.4010 | 1325 | 0.0165 | |
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| 0.0059 | 6.5217 | 1350 | 0.0163 | |
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| 0.0057 | 6.6425 | 1375 | 0.0151 | |
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| 0.0061 | 6.7633 | 1400 | 0.0164 | |
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| 0.006 | 6.8841 | 1425 | 0.0156 | |
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| 0.0062 | 7.0048 | 1450 | 0.0161 | |
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| 0.006 | 7.1256 | 1475 | 0.0178 | |
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| 0.0059 | 7.2464 | 1500 | 0.0169 | |
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| 0.0043 | 7.3671 | 1525 | 0.0175 | |
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| 0.0049 | 7.4879 | 1550 | 0.0178 | |
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| 0.0058 | 7.6087 | 1575 | 0.0156 | |
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| 0.0062 | 7.7295 | 1600 | 0.0158 | |
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| 0.0045 | 7.8502 | 1625 | 0.0151 | |
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| 0.0054 | 7.9710 | 1650 | 0.0150 | |
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| 0.0042 | 8.0918 | 1675 | 0.0157 | |
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| 0.0039 | 8.2126 | 1700 | 0.0157 | |
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| 0.0046 | 8.3333 | 1725 | 0.0170 | |
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| 0.0025 | 8.4541 | 1750 | 0.0154 | |
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| 0.0047 | 8.5749 | 1775 | 0.0156 | |
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| 0.0044 | 8.6957 | 1800 | 0.0166 | |
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| 0.0031 | 8.8164 | 1825 | 0.0172 | |
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| 0.0029 | 8.9372 | 1850 | 0.0167 | |
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| 0.0032 | 9.0580 | 1875 | 0.0169 | |
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| 0.0036 | 9.1787 | 1900 | 0.0167 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.46.1 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
