metadata
license: other
base_model: meta-llama/Meta-Llama-3-8B
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: C014_llama3-8b-base_pretrain_20240428_005832
results: []
C014_llama3-8b-base_pretrain_20240428_005832
This model is a fine-tuned version of /mnt/models-pku/progressalign/shared_storage/downloaded_models/llama3-8b-base on the C014_data dataset. It achieves the following results on the evaluation set:
- Loss: 2.2045
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1.5e-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 64
- total_eval_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: polynomial
- lr_scheduler_warmup_steps: 20
- num_epochs: 4.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.5789 | 0.0152 | 1 | 2.6458 |
| 2.5672 | 0.0758 | 5 | 2.6280 |
| 2.5751 | 0.1515 | 10 | 2.5314 |
| 2.418 | 0.2273 | 15 | 2.4634 |
| 2.4701 | 0.3030 | 20 | 2.4177 |
| 2.3904 | 0.3788 | 25 | 2.3785 |
| 2.3539 | 0.4545 | 30 | 2.3378 |
| 2.3101 | 0.5303 | 35 | 2.3082 |
| 2.3254 | 0.6061 | 40 | 2.2816 |
| 2.2762 | 0.6818 | 45 | 2.2614 |
| 2.2525 | 0.7576 | 50 | 2.2458 |
| 2.2777 | 0.8333 | 55 | 2.2321 |
| 2.2054 | 0.9091 | 60 | 2.2206 |
| 2.237 | 0.9848 | 65 | 2.2113 |
| 1.986 | 1.0606 | 70 | 2.2115 |
| 1.9373 | 1.1364 | 75 | 2.2217 |
| 1.9228 | 1.2121 | 80 | 2.2132 |
| 1.9084 | 1.2879 | 85 | 2.2118 |
| 1.9684 | 1.3636 | 90 | 2.2122 |
| 1.9126 | 1.4394 | 95 | 2.2094 |
| 1.9101 | 1.5152 | 100 | 2.2066 |
| 1.8496 | 1.5909 | 105 | 2.2058 |
| 1.9154 | 1.6667 | 110 | 2.2057 |
| 1.9233 | 1.7424 | 115 | 2.2056 |
| 1.9198 | 1.8182 | 120 | 2.2052 |
| 1.9229 | 1.8939 | 125 | 2.2048 |
| 1.8913 | 1.9697 | 130 | 2.2045 |
| 1.8814 | 2.0455 | 135 | 2.2046 |
| 1.8813 | 2.1212 | 140 | 2.2051 |
| 1.8912 | 2.1970 | 145 | 2.2058 |
| 1.9184 | 2.2727 | 150 | 2.2065 |
| 1.8662 | 2.3485 | 155 | 2.2071 |
| 1.8809 | 2.4242 | 160 | 2.2074 |
| 1.8591 | 2.5 | 165 | 2.2077 |
| 1.8731 | 2.5758 | 170 | 2.2079 |
| 1.8948 | 2.6515 | 175 | 2.2082 |
| 1.8876 | 2.7273 | 180 | 2.2082 |
| 1.8408 | 2.8030 | 185 | 2.2083 |
| 1.8931 | 2.8788 | 190 | 2.2082 |
| 1.8569 | 2.9545 | 195 | 2.2080 |
| 1.8621 | 3.0303 | 200 | 2.2079 |
| 1.8863 | 3.1061 | 205 | 2.2078 |
| 1.9021 | 3.1818 | 210 | 2.2079 |
| 1.8648 | 3.2576 | 215 | 2.2080 |
| 1.8443 | 3.3333 | 220 | 2.2081 |
| 1.8978 | 3.4091 | 225 | 2.2080 |
| 1.8658 | 3.4848 | 230 | 2.2080 |
| 1.8706 | 3.5606 | 235 | 2.2079 |
| 1.8855 | 3.6364 | 240 | 2.2078 |
| 1.8535 | 3.7121 | 245 | 2.2078 |
| 1.9062 | 3.7879 | 250 | 2.2079 |
| 1.8628 | 3.8636 | 255 | 2.2078 |
| 1.8484 | 3.9394 | 260 | 2.2077 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.1.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1