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--- |
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license: llama2 |
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base_model: meta-llama/CodeLlama-34b-Instruct-hf |
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tags: |
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- alignment-handbook |
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- generated_from_trainer |
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datasets: |
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- meng-lab/CodeLlama-34B-Instruct-humaneval |
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model-index: |
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- name: CodeLlama-34b-Instruct-sft-5e-3-epoch-100-human-eval-final |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/uva-llm/huggingface/runs/93nixyw1) |
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# CodeLlama-34b-Instruct-sft-5e-3-epoch-100-human-eval-final |
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This model is a fine-tuned version of [meta-llama/CodeLlama-34b-Instruct-hf](https://huggingface.co/meta-llama/CodeLlama-34b-Instruct-hf) on the meng-lab/CodeLlama-34B-Instruct-humaneval dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 3.7616 |
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- Loss Layer 6 Head: 1.0709 |
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- Loss Layer 12 Head: 0.8047 |
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- Loss Layer 18 Head: 0.7212 |
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- Loss Layer 24 Head: 0.4396 |
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- Loss Layer 30 Head: 0.3042 |
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- Loss Layer 36 Head: 0.2040 |
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- Loss Layer 42 Head: 0.1346 |
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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: 0.005 |
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- train_batch_size: 1 |
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- eval_batch_size: 2 |
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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: 16 |
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- total_train_batch_size: 128 |
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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_ratio: 0.1 |
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- num_epochs: 100 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Loss Layer 6 Head | Loss Layer 12 Head | Loss Layer 18 Head | Loss Layer 24 Head | Loss Layer 30 Head | Loss Layer 36 Head | Loss Layer 42 Head | |
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|:-------------:|:-------:|:----:|:---------------:|:-----------------:|:------------------:|:------------------:|:------------------:|:------------------:|:------------------:|:------------------:| |
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| 3.7028 | 9.1168 | 200 | 4.6352 | 1.4035 | 0.8311 | 1.0429 | 0.4931 | 0.4457 | 0.2349 | 0.1599 | |
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| 2.736 | 18.2336 | 400 | 4.7219 | 1.2158 | 0.8316 | 0.7490 | 1.0869 | 0.3238 | 0.2666 | 0.1723 | |
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| 2.0128 | 27.3504 | 600 | 3.8953 | 1.1598 | 0.8030 | 0.7230 | 0.4451 | 0.3500 | 0.2027 | 0.1459 | |
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| 3.3605 | 36.4672 | 800 | 4.9203 | 1.1038 | 0.8175 | 1.6655 | 0.4410 | 0.3091 | 0.2055 | 0.1365 | |
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| 2.5177 | 45.5840 | 1000 | 4.2388 | 1.0907 | 0.8042 | 1.1115 | 0.4403 | 0.3038 | 0.2217 | 0.1412 | |
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| 2.0743 | 54.7009 | 1200 | 3.9221 | 1.0727 | 0.8050 | 0.8689 | 0.4418 | 0.3012 | 0.2044 | 0.1362 | |
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| 1.8844 | 63.8177 | 1400 | 3.8140 | 1.0723 | 0.8028 | 0.7729 | 0.4389 | 0.3045 | 0.2036 | 0.1350 | |
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| 1.8019 | 72.9345 | 1600 | 3.7777 | 1.0726 | 0.8038 | 0.7376 | 0.4401 | 0.3042 | 0.2032 | 0.1345 | |
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| 1.7339 | 82.0513 | 1800 | 3.7662 | 1.0703 | 0.8056 | 0.7246 | 0.4394 | 0.3041 | 0.2042 | 0.1347 | |
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| 1.6981 | 91.1681 | 2000 | 3.7616 | 1.0709 | 0.8047 | 0.7212 | 0.4396 | 0.3042 | 0.2040 | 0.1346 | |
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### Framework versions |
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- Transformers 4.43.2 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.2.0 |
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- Tokenizers 0.19.1 |
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