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--- |
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base_model: meta-llama/Meta-Llama-3.1-8B-Instruct |
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library_name: peft |
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license: llama3.1 |
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tags: |
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- trl |
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- sft |
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- generated_from_trainer |
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model-index: |
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- name: Llama-31-8B_task-2_60-samples_config-4_full |
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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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# Llama-31-8B_task-2_60-samples_config-4_full |
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This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co./meta-llama/Meta-Llama-3.1-8B-Instruct) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0840 |
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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-05 |
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- train_batch_size: 1 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- gradient_accumulation_steps: 16 |
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- total_train_batch_size: 16 |
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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: 150 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-------:|:----:|:---------------:| |
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| 1.5658 | 0.6957 | 2 | 1.5854 | |
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| 1.5728 | 1.7391 | 5 | 1.5836 | |
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| 1.583 | 2.7826 | 8 | 1.5803 | |
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| 1.562 | 3.8261 | 11 | 1.5753 | |
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| 1.5687 | 4.8696 | 14 | 1.5688 | |
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| 1.5495 | 5.9130 | 17 | 1.5600 | |
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| 1.5493 | 6.9565 | 20 | 1.5482 | |
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| 1.5379 | 8.0 | 23 | 1.5340 | |
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| 1.5155 | 8.6957 | 25 | 1.5222 | |
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| 1.5131 | 9.7391 | 28 | 1.5057 | |
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| 1.4971 | 10.7826 | 31 | 1.4859 | |
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| 1.4675 | 11.8261 | 34 | 1.4652 | |
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| 1.4518 | 12.8696 | 37 | 1.4474 | |
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| 1.4267 | 13.9130 | 40 | 1.4301 | |
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| 1.4004 | 14.9565 | 43 | 1.4132 | |
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| 1.3993 | 16.0 | 46 | 1.3976 | |
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| 1.3748 | 16.6957 | 48 | 1.3881 | |
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| 1.3664 | 17.7391 | 51 | 1.3743 | |
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| 1.3465 | 18.7826 | 54 | 1.3614 | |
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| 1.3407 | 19.8261 | 57 | 1.3488 | |
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| 1.32 | 20.8696 | 60 | 1.3369 | |
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| 1.305 | 21.9130 | 63 | 1.3247 | |
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| 1.281 | 22.9565 | 66 | 1.3119 | |
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| 1.2869 | 24.0 | 69 | 1.2986 | |
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| 1.2523 | 24.6957 | 71 | 1.2903 | |
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| 1.2642 | 25.7391 | 74 | 1.2783 | |
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| 1.2323 | 26.7826 | 77 | 1.2657 | |
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| 1.2121 | 27.8261 | 80 | 1.2535 | |
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| 1.1896 | 28.8696 | 83 | 1.2410 | |
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| 1.1678 | 29.9130 | 86 | 1.2283 | |
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| 1.1768 | 30.9565 | 89 | 1.2154 | |
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| 1.1824 | 32.0 | 92 | 1.2030 | |
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| 1.1589 | 32.6957 | 94 | 1.1948 | |
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| 1.126 | 33.7391 | 97 | 1.1820 | |
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| 1.1059 | 34.7826 | 100 | 1.1694 | |
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| 1.1334 | 35.8261 | 103 | 1.1582 | |
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| 1.1081 | 36.8696 | 106 | 1.1483 | |
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| 1.0794 | 37.9130 | 109 | 1.1392 | |
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| 1.0614 | 38.9565 | 112 | 1.1315 | |
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| 1.0877 | 40.0 | 115 | 1.1259 | |
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| 1.0198 | 40.6957 | 117 | 1.1229 | |
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| 1.0538 | 41.7391 | 120 | 1.1193 | |
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| 1.0351 | 42.7826 | 123 | 1.1165 | |
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| 1.0121 | 43.8261 | 126 | 1.1144 | |
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| 1.0475 | 44.8696 | 129 | 1.1125 | |
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| 1.035 | 45.9130 | 132 | 1.1105 | |
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| 1.0582 | 46.9565 | 135 | 1.1090 | |
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| 1.029 | 48.0 | 138 | 1.1072 | |
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| 1.0353 | 48.6957 | 140 | 1.1064 | |
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| 1.0203 | 49.7391 | 143 | 1.1048 | |
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| 1.0313 | 50.7826 | 146 | 1.1035 | |
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| 1.0473 | 51.8261 | 149 | 1.1026 | |
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| 1.0189 | 52.8696 | 152 | 1.1011 | |
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| 1.0088 | 53.9130 | 155 | 1.1001 | |
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| 1.0336 | 54.9565 | 158 | 1.0989 | |
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| 1.0014 | 56.0 | 161 | 1.0981 | |
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| 1.0036 | 56.6957 | 163 | 1.0972 | |
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| 1.0266 | 57.7391 | 166 | 1.0962 | |
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| 0.9893 | 58.7826 | 169 | 1.0956 | |
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| 1.0122 | 59.8261 | 172 | 1.0948 | |
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| 1.0456 | 60.8696 | 175 | 1.0939 | |
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| 0.9873 | 61.9130 | 178 | 1.0933 | |
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| 1.0189 | 62.9565 | 181 | 1.0926 | |
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| 1.0325 | 64.0 | 184 | 1.0918 | |
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| 1.0081 | 64.6957 | 186 | 1.0912 | |
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| 0.995 | 65.7391 | 189 | 1.0908 | |
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| 1.0104 | 66.7826 | 192 | 1.0903 | |
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| 0.9979 | 67.8261 | 195 | 1.0896 | |
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| 0.9927 | 68.8696 | 198 | 1.0893 | |
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| 0.9898 | 69.9130 | 201 | 1.0887 | |
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| 1.0087 | 70.9565 | 204 | 1.0882 | |
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| 0.9903 | 72.0 | 207 | 1.0878 | |
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| 1.0198 | 72.6957 | 209 | 1.0877 | |
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| 1.0078 | 73.7391 | 212 | 1.0874 | |
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| 1.0056 | 74.7826 | 215 | 1.0870 | |
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| 1.0114 | 75.8261 | 218 | 1.0867 | |
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| 0.9982 | 76.8696 | 221 | 1.0864 | |
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| 1.0105 | 77.9130 | 224 | 1.0860 | |
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| 1.0033 | 78.9565 | 227 | 1.0859 | |
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| 1.0024 | 80.0 | 230 | 1.0858 | |
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| 1.0091 | 80.6957 | 232 | 1.0855 | |
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| 0.9971 | 81.7391 | 235 | 1.0853 | |
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| 0.969 | 82.7826 | 238 | 1.0851 | |
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| 1.0242 | 83.8261 | 241 | 1.0847 | |
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| 0.9949 | 84.8696 | 244 | 1.0850 | |
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| 0.9715 | 85.9130 | 247 | 1.0847 | |
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| 1.0164 | 86.9565 | 250 | 1.0846 | |
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| 0.9729 | 88.0 | 253 | 1.0845 | |
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| 1.0065 | 88.6957 | 255 | 1.0845 | |
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| 0.994 | 89.7391 | 258 | 1.0845 | |
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| 0.9852 | 90.7826 | 261 | 1.0843 | |
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| 0.9755 | 91.8261 | 264 | 1.0842 | |
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| 1.0191 | 92.8696 | 267 | 1.0839 | |
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| 0.9864 | 93.9130 | 270 | 1.0841 | |
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| 0.9773 | 94.9565 | 273 | 1.0841 | |
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| 0.9869 | 96.0 | 276 | 1.0842 | |
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| 0.986 | 96.6957 | 278 | 1.0841 | |
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| 0.9925 | 97.7391 | 281 | 1.0840 | |
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| 0.9882 | 98.7826 | 284 | 1.0840 | |
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| 0.9917 | 99.8261 | 287 | 1.0840 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.44.0 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
