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--- |
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base_model: NousResearch/Meta-Llama-3.1-8B-Instruct |
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datasets: |
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- generator |
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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: llama381binstruct_summarize_short |
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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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# llama381binstruct_summarize_short |
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This model is a fine-tuned version of [NousResearch/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/NousResearch/Meta-Llama-3.1-8B-Instruct) on the generator dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.4596 |
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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: 0.0002 |
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- train_batch_size: 1 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 30 |
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- training_steps: 400 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-------:|:----:|:---------------:| |
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| 1.7476 | 1.3158 | 25 | 1.4853 | |
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| 0.7367 | 2.6316 | 50 | 1.5640 | |
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| 0.3774 | 3.9474 | 75 | 1.7475 | |
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| 0.1429 | 5.2632 | 100 | 1.9993 | |
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| 0.086 | 6.5789 | 125 | 2.0531 | |
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| 0.0375 | 7.8947 | 150 | 2.1944 | |
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| 0.0224 | 9.2105 | 175 | 2.3234 | |
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| 0.0096 | 10.5263 | 200 | 2.1743 | |
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| 0.0053 | 11.8421 | 225 | 2.2676 | |
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| 0.0035 | 13.1579 | 250 | 2.4019 | |
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| 0.005 | 14.4737 | 275 | 2.4052 | |
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| 0.003 | 15.7895 | 300 | 2.4257 | |
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| 0.0025 | 17.1053 | 325 | 2.4432 | |
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| 0.0025 | 18.4211 | 350 | 2.4528 | |
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| 0.0022 | 19.7368 | 375 | 2.4576 | |
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| 0.0022 | 21.0526 | 400 | 2.4596 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.44.2 |
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- Pytorch 2.4.0+cu121 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
