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--- |
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base_model: meta-llama/Meta-Llama-3.1-8B-Instruct |
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datasets: |
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- barc0/induction_100k_gpt4o-mini_generated_problems_seed100.jsonl_messages_format_0.3 |
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library_name: peft |
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license: llama3.1 |
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tags: |
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- alignment-handbook |
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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: barc-llama3.1-8b-instruct-lora64-induction-gpt4mini20k_lr2e-4_epoch3 |
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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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# barc-llama3.1-8b-instruct-lora64-induction-gpt4mini20k_lr2e-4_epoch3 |
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This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct) on the barc0/induction_100k_gpt4o-mini_generated_problems_seed100.jsonl_messages_format_0.3 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3327 |
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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: 8 |
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- eval_batch_size: 4 |
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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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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 128 |
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- total_eval_batch_size: 32 |
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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_ratio: 0.1 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.3519 | 1.0 | 152 | 0.3529 | |
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| 0.3233 | 2.0 | 304 | 0.3357 | |
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| 0.2989 | 3.0 | 456 | 0.3327 | |
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### Framework versions |
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- PEFT 0.13.0 |
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- Transformers 4.45.0.dev0 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
