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--- |
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base_model: bigcode/starcoderbase-7b |
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library_name: peft |
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license: bigcode-openrail-m |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: peft-starcoder-lora-cutlass |
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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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# peft-starcoder-lora-cutlass |
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This model is a fine-tuned version of [bigcode/starcoderbase-7b](https://huggingface.co/bigcode/starcoderbase-7b) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4322 |
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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: 0.0005 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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: cosine |
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- lr_scheduler_warmup_steps: 30 |
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- training_steps: 4000 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.5409 | 0.025 | 100 | 0.4729 | |
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| 0.3672 | 0.05 | 200 | 0.4051 | |
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| 0.3432 | 0.075 | 300 | 0.3876 | |
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| 0.312 | 0.1 | 400 | 0.3548 | |
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| 0.2594 | 0.125 | 500 | 0.3507 | |
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| 0.2821 | 0.15 | 600 | 0.3428 | |
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| 0.1958 | 0.175 | 700 | 0.3391 | |
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| 0.2362 | 0.2 | 800 | 0.3405 | |
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| 0.209 | 0.225 | 900 | 0.3421 | |
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| 0.2114 | 0.25 | 1000 | 0.3481 | |
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| 0.1877 | 0.275 | 1100 | 0.3447 | |
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| 0.1903 | 0.3 | 1200 | 0.3533 | |
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| 0.1723 | 0.325 | 1300 | 0.3578 | |
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| 0.1465 | 0.35 | 1400 | 0.3643 | |
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| 0.1751 | 0.375 | 1500 | 0.3639 | |
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| 0.1213 | 0.4 | 1600 | 0.3749 | |
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| 0.119 | 0.425 | 1700 | 0.3692 | |
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| 0.1199 | 0.45 | 1800 | 0.3820 | |
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| 0.0986 | 0.475 | 1900 | 0.3816 | |
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| 0.1232 | 0.5 | 2000 | 0.3868 | |
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| 0.0819 | 0.525 | 2100 | 0.3923 | |
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| 0.096 | 0.55 | 2200 | 0.3964 | |
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| 0.0873 | 0.575 | 2300 | 0.3977 | |
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| 0.0892 | 0.6 | 2400 | 0.4007 | |
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| 0.0802 | 0.625 | 2500 | 0.4078 | |
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| 0.066 | 0.65 | 2600 | 0.4119 | |
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| 0.0863 | 0.675 | 2700 | 0.4125 | |
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| 0.0722 | 0.7 | 2800 | 0.4189 | |
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| 0.0888 | 0.725 | 2900 | 0.4201 | |
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| 0.0757 | 0.75 | 3000 | 0.4263 | |
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| 0.0666 | 0.775 | 3100 | 0.4234 | |
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| 0.0757 | 0.8 | 3200 | 0.4275 | |
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| 0.053 | 0.825 | 3300 | 0.4289 | |
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| 0.0772 | 0.85 | 3400 | 0.4290 | |
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| 0.0546 | 0.875 | 3500 | 0.4297 | |
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| 0.0601 | 0.9 | 3600 | 0.4311 | |
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| 0.0606 | 0.925 | 3700 | 0.4317 | |
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| 0.0544 | 0.95 | 3800 | 0.4314 | |
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| 0.065 | 0.975 | 3900 | 0.4320 | |
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| 0.0503 | 1.0 | 4000 | 0.4322 | |
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### Framework versions |
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- PEFT 0.11.1 |
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- Transformers 4.42.4 |
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- Pytorch 2.4.0a0+07cecf4168.nv24.05 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
