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--- |
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license: other |
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library_name: peft |
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tags: |
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- llama-factory |
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- lora |
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- generated_from_trainer |
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base_model: /data1/model/llama2/meta-llama/Llama2-13b |
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model-index: |
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- name: alpaca_no_sys |
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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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# alpaca_no_sys |
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This model is a fine-tuned version of [/data1/model/llama2/meta-llama/Llama2-13b](https://huggingface.co//data1/model/llama2/meta-llama/Llama2-13b) on the alpaca_no_sys dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.0082 |
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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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- distributed_type: multi-GPU |
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- num_devices: 2 |
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- total_train_batch_size: 16 |
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- total_eval_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_steps: 20 |
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- num_epochs: 10.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 1.0429 | 0.07 | 200 | 1.0298 | |
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| 1.0505 | 0.14 | 400 | 1.0238 | |
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| 1.044 | 0.22 | 600 | 1.0194 | |
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| 1.0169 | 0.29 | 800 | 1.0172 | |
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| 1.02 | 0.36 | 1000 | 1.0154 | |
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| 0.9492 | 0.43 | 1200 | 1.0134 | |
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| 1.0051 | 0.51 | 1400 | 1.0117 | |
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| 1.0469 | 0.58 | 1600 | 1.0106 | |
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| 0.9994 | 0.65 | 1800 | 1.0094 | |
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| 1.0141 | 0.72 | 2000 | 1.0082 | |
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| 1.0891 | 0.8 | 2200 | 1.0073 | |
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| 1.0141 | 0.87 | 2400 | 1.0063 | |
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| 1.0002 | 0.94 | 2600 | 1.0059 | |
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| 0.9686 | 1.01 | 2800 | 1.0086 | |
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| 0.9767 | 1.09 | 3000 | 1.0141 | |
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| 0.9494 | 1.16 | 3200 | 1.0160 | |
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### Framework versions |
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- PEFT 0.9.0 |
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- Transformers 4.38.2 |
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- Pytorch 2.2.1 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
