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--- |
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license: llama2 |
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base_model: Phind/Phind-CodeLlama-34B-v2 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: qlora-out |
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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/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl) |
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# qlora-out |
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This model is a fine-tuned version of [Phind/Phind-CodeLlama-34B-v2](https://huggingface.co/Phind/Phind-CodeLlama-34B-v2) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: nan |
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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: 1 |
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- seed: 42 |
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- distributed_type: multi-GPU |
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- num_devices: 6 |
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- gradient_accumulation_steps: 3 |
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- total_train_batch_size: 18 |
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- total_eval_batch_size: 6 |
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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: 10 |
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- num_epochs: 2 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.2069 | 0.1 | 20 | nan | |
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| 0.0986 | 0.21 | 40 | nan | |
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| 0.1101 | 0.31 | 60 | nan | |
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| 0.072 | 0.41 | 80 | nan | |
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| 0.1258 | 0.52 | 100 | nan | |
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| 0.0675 | 0.62 | 120 | nan | |
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| 0.0728 | 0.72 | 140 | nan | |
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| 0.115 | 0.83 | 160 | nan | |
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| 0.0769 | 0.93 | 180 | nan | |
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| 0.0609 | 1.03 | 200 | nan | |
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| 0.0881 | 1.14 | 220 | nan | |
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| 0.0674 | 1.24 | 240 | nan | |
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| 0.0476 | 1.34 | 260 | nan | |
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| 0.0259 | 1.45 | 280 | nan | |
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| 0.0534 | 1.55 | 300 | nan | |
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| 0.0449 | 1.65 | 320 | nan | |
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| 0.0325 | 1.76 | 340 | nan | |
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| 0.03 | 1.86 | 360 | nan | |
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| 0.0416 | 1.96 | 380 | nan | |
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### Framework versions |
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- Transformers 4.35.0.dev0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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