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--- |
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license: llama2 |
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library_name: peft |
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tags: |
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- unsloth |
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- generated_from_trainer |
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base_model: meta-llama/Llama-2-13b-hf |
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model-index: |
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- name: llama_2_13b_Magiccoder_evol_10k_reverse |
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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_2_13b_Magiccoder_evol_10k_reverse |
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This model is a fine-tuned version of [meta-llama/Llama-2-13b-hf](https://huggingface.co/meta-llama/Llama-2-13b-hf) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0887 |
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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: 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_steps: 0.02 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:------:|:----:|:---------------:| |
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| 1.173 | 0.0262 | 4 | 1.1853 | |
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| 1.1716 | 0.0523 | 8 | 1.1587 | |
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| 1.105 | 0.0785 | 12 | 1.1410 | |
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| 1.0534 | 0.1047 | 16 | 1.1289 | |
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| 1.0911 | 0.1308 | 20 | 1.1239 | |
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| 1.0565 | 0.1570 | 24 | 1.1172 | |
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| 1.0589 | 0.1832 | 28 | 1.1140 | |
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| 1.1027 | 0.2093 | 32 | 1.1106 | |
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| 1.0379 | 0.2355 | 36 | 1.1096 | |
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| 1.1134 | 0.2617 | 40 | 1.1087 | |
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| 1.0969 | 0.2878 | 44 | 1.1049 | |
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| 1.1361 | 0.3140 | 48 | 1.1056 | |
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| 1.1121 | 0.3401 | 52 | 1.1023 | |
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| 1.0828 | 0.3663 | 56 | 1.1047 | |
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| 1.1246 | 0.3925 | 60 | 1.1027 | |
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| 1.1285 | 0.4186 | 64 | 1.0990 | |
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| 1.0788 | 0.4448 | 68 | 1.0998 | |
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| 1.0917 | 0.4710 | 72 | 1.0950 | |
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| 1.0395 | 0.4971 | 76 | 1.0977 | |
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| 1.1267 | 0.5233 | 80 | 1.0954 | |
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| 1.1414 | 0.5495 | 84 | 1.0955 | |
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| 1.0821 | 0.5756 | 88 | 1.0930 | |
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| 1.0277 | 0.6018 | 92 | 1.0908 | |
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| 1.0303 | 0.6280 | 96 | 1.0917 | |
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| 1.0947 | 0.6541 | 100 | 1.0905 | |
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| 1.0824 | 0.6803 | 104 | 1.0903 | |
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| 1.0726 | 0.7065 | 108 | 1.0912 | |
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| 1.1064 | 0.7326 | 112 | 1.0907 | |
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| 1.0467 | 0.7588 | 116 | 1.0892 | |
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| 1.0725 | 0.7850 | 120 | 1.0885 | |
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| 1.09 | 0.8111 | 124 | 1.0893 | |
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| 1.0506 | 0.8373 | 128 | 1.0900 | |
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| 0.9951 | 0.8635 | 132 | 1.0902 | |
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| 1.1032 | 0.8896 | 136 | 1.0895 | |
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| 1.0116 | 0.9158 | 140 | 1.0891 | |
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| 1.0683 | 0.9419 | 144 | 1.0889 | |
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| 1.0902 | 0.9681 | 148 | 1.0888 | |
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| 1.0721 | 0.9943 | 152 | 1.0887 | |
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### Framework versions |
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- PEFT 0.7.1 |
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- Transformers 4.40.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
