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--- |
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license: other |
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base_model: meta-llama/Meta-Llama-3-8B |
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tags: |
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- llama-factory |
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- full |
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- generated_from_trainer |
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model-index: |
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- name: C014_llama3-8b-base_pretrain_20240428_005832 |
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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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# C014_llama3-8b-base_pretrain_20240428_005832 |
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This model is a fine-tuned version of [/mnt/models-pku/progressalign/shared_storage/downloaded_models/llama3-8b-base](https://huggingface.co//mnt/models-pku/progressalign/shared_storage/downloaded_models/llama3-8b-base) on the C014_data dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.2045 |
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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: 1.5e-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: 8 |
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- total_train_batch_size: 64 |
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- total_eval_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: polynomial |
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- lr_scheduler_warmup_steps: 20 |
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- num_epochs: 4.0 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 2.5789 | 0.0152 | 1 | 2.6458 | |
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| 2.5672 | 0.0758 | 5 | 2.6280 | |
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| 2.5751 | 0.1515 | 10 | 2.5314 | |
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| 2.418 | 0.2273 | 15 | 2.4634 | |
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| 2.4701 | 0.3030 | 20 | 2.4177 | |
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| 2.3904 | 0.3788 | 25 | 2.3785 | |
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| 2.3539 | 0.4545 | 30 | 2.3378 | |
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| 2.3101 | 0.5303 | 35 | 2.3082 | |
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| 2.3254 | 0.6061 | 40 | 2.2816 | |
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| 2.2762 | 0.6818 | 45 | 2.2614 | |
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| 2.2525 | 0.7576 | 50 | 2.2458 | |
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| 2.2777 | 0.8333 | 55 | 2.2321 | |
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| 2.2054 | 0.9091 | 60 | 2.2206 | |
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| 2.237 | 0.9848 | 65 | 2.2113 | |
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| 1.986 | 1.0606 | 70 | 2.2115 | |
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| 1.9373 | 1.1364 | 75 | 2.2217 | |
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| 1.9228 | 1.2121 | 80 | 2.2132 | |
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| 1.9084 | 1.2879 | 85 | 2.2118 | |
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| 1.9684 | 1.3636 | 90 | 2.2122 | |
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| 1.9126 | 1.4394 | 95 | 2.2094 | |
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| 1.9101 | 1.5152 | 100 | 2.2066 | |
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| 1.8496 | 1.5909 | 105 | 2.2058 | |
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| 1.9154 | 1.6667 | 110 | 2.2057 | |
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| 1.9233 | 1.7424 | 115 | 2.2056 | |
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| 1.9198 | 1.8182 | 120 | 2.2052 | |
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| 1.9229 | 1.8939 | 125 | 2.2048 | |
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| 1.8913 | 1.9697 | 130 | 2.2045 | |
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| 1.8814 | 2.0455 | 135 | 2.2046 | |
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| 1.8813 | 2.1212 | 140 | 2.2051 | |
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| 1.8912 | 2.1970 | 145 | 2.2058 | |
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| 1.9184 | 2.2727 | 150 | 2.2065 | |
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| 1.8662 | 2.3485 | 155 | 2.2071 | |
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| 1.8809 | 2.4242 | 160 | 2.2074 | |
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| 1.8591 | 2.5 | 165 | 2.2077 | |
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| 1.8731 | 2.5758 | 170 | 2.2079 | |
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| 1.8948 | 2.6515 | 175 | 2.2082 | |
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| 1.8876 | 2.7273 | 180 | 2.2082 | |
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| 1.8408 | 2.8030 | 185 | 2.2083 | |
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| 1.8931 | 2.8788 | 190 | 2.2082 | |
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| 1.8569 | 2.9545 | 195 | 2.2080 | |
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| 1.8621 | 3.0303 | 200 | 2.2079 | |
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| 1.8863 | 3.1061 | 205 | 2.2078 | |
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| 1.9021 | 3.1818 | 210 | 2.2079 | |
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| 1.8648 | 3.2576 | 215 | 2.2080 | |
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| 1.8443 | 3.3333 | 220 | 2.2081 | |
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| 1.8978 | 3.4091 | 225 | 2.2080 | |
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| 1.8658 | 3.4848 | 230 | 2.2080 | |
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| 1.8706 | 3.5606 | 235 | 2.2079 | |
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| 1.8855 | 3.6364 | 240 | 2.2078 | |
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| 1.8535 | 3.7121 | 245 | 2.2078 | |
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| 1.9062 | 3.7879 | 250 | 2.2079 | |
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| 1.8628 | 3.8636 | 255 | 2.2078 | |
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| 1.8484 | 3.9394 | 260 | 2.2077 | |
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### Framework versions |
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- Transformers 4.40.0 |
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- Pytorch 2.1.2+cu121 |
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- Datasets 2.18.0 |
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- Tokenizers 0.19.1 |
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