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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: codeparrot-small-custom-functions-dataset-python |
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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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# codeparrot-small-custom-functions-dataset-python |
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This model is a fine-tuned version of [codeparrot/codeparrot-small](https://huggingface.co./codeparrot/codeparrot-small) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4238 |
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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: 2e-05 |
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- train_batch_size: 8 |
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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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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 1.216 | 0.12 | 1 | 1.0747 | |
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| 1.051 | 0.25 | 2 | 1.0005 | |
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| 0.9855 | 0.38 | 3 | 0.9462 | |
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| 0.9259 | 0.5 | 4 | 0.9042 | |
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| 0.9236 | 0.62 | 5 | 0.8675 | |
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| 0.8644 | 0.75 | 6 | 0.8331 | |
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| 0.8148 | 0.88 | 7 | 0.8030 | |
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| 0.7554 | 1.0 | 8 | 0.7800 | |
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| 0.7815 | 1.12 | 9 | 0.7600 | |
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| 0.784 | 1.25 | 10 | 0.7440 | |
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| 0.635 | 1.38 | 11 | 0.7309 | |
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| 0.6666 | 1.5 | 12 | 0.7170 | |
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| 0.7676 | 1.62 | 13 | 0.6993 | |
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| 0.6608 | 1.75 | 14 | 0.6835 | |
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| 0.6885 | 1.88 | 15 | 0.6696 | |
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| 0.69 | 2.0 | 16 | 0.6582 | |
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| 0.6343 | 2.12 | 17 | 0.6463 | |
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| 0.709 | 2.25 | 18 | 0.6324 | |
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| 0.5446 | 2.38 | 19 | 0.6206 | |
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| 0.5298 | 2.5 | 20 | 0.6102 | |
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| 0.6478 | 2.62 | 21 | 0.6016 | |
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| 0.546 | 2.75 | 22 | 0.5941 | |
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| 0.6297 | 2.88 | 23 | 0.5871 | |
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| 0.4518 | 3.0 | 24 | 0.5814 | |
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| 0.566 | 3.12 | 25 | 0.5769 | |
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| 0.6285 | 3.25 | 26 | 0.5702 | |
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| 0.5938 | 3.38 | 27 | 0.5631 | |
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| 0.514 | 3.5 | 28 | 0.5568 | |
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| 0.5113 | 3.62 | 29 | 0.5504 | |
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| 0.512 | 3.75 | 30 | 0.5451 | |
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| 0.4392 | 3.88 | 31 | 0.5407 | |
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| 0.5097 | 4.0 | 32 | 0.5370 | |
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| 0.4866 | 4.12 | 33 | 0.5326 | |
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| 0.5028 | 4.25 | 34 | 0.5285 | |
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| 0.5438 | 4.38 | 35 | 0.5228 | |
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| 0.5424 | 4.5 | 36 | 0.5166 | |
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| 0.5156 | 4.62 | 37 | 0.5108 | |
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| 0.4335 | 4.75 | 38 | 0.5056 | |
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| 0.4298 | 4.88 | 39 | 0.5013 | |
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| 0.5268 | 5.0 | 40 | 0.4978 | |
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| 0.4714 | 5.12 | 41 | 0.4938 | |
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| 0.4659 | 5.25 | 42 | 0.4907 | |
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| 0.4573 | 5.38 | 43 | 0.4874 | |
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| 0.4689 | 5.5 | 44 | 0.4847 | |
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| 0.4346 | 5.62 | 45 | 0.4824 | |
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| 0.4563 | 5.75 | 46 | 0.4794 | |
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| 0.4505 | 5.88 | 47 | 0.4761 | |
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| 0.7359 | 6.0 | 48 | 0.4732 | |
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| 0.4704 | 6.12 | 49 | 0.4706 | |
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| 0.4223 | 6.25 | 50 | 0.4685 | |
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| 0.4789 | 6.38 | 51 | 0.4651 | |
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| 0.4402 | 6.5 | 52 | 0.4624 | |
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| 0.4454 | 6.62 | 53 | 0.4597 | |
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| 0.4496 | 6.75 | 54 | 0.4566 | |
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| 0.3942 | 6.88 | 55 | 0.4539 | |
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| 0.2915 | 7.0 | 56 | 0.4515 | |
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| 0.3926 | 7.12 | 57 | 0.4496 | |
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| 0.4102 | 7.25 | 58 | 0.4474 | |
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| 0.4235 | 7.38 | 59 | 0.4456 | |
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| 0.4841 | 7.5 | 60 | 0.4441 | |
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| 0.3914 | 7.62 | 61 | 0.4423 | |
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| 0.4417 | 7.75 | 62 | 0.4404 | |
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| 0.4212 | 7.88 | 63 | 0.4384 | |
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| 0.4343 | 8.0 | 64 | 0.4369 | |
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| 0.4159 | 8.12 | 65 | 0.4355 | |
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| 0.4193 | 8.25 | 66 | 0.4343 | |
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| 0.4393 | 8.38 | 67 | 0.4333 | |
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| 0.4507 | 8.5 | 68 | 0.4319 | |
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| 0.3855 | 8.62 | 69 | 0.4305 | |
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| 0.4064 | 8.75 | 70 | 0.4293 | |
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| 0.4044 | 8.88 | 71 | 0.4283 | |
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| 0.2957 | 9.0 | 72 | 0.4275 | |
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| 0.4442 | 9.12 | 73 | 0.4266 | |
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| 0.4142 | 9.25 | 74 | 0.4260 | |
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| 0.4022 | 9.38 | 75 | 0.4253 | |
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| 0.4161 | 9.5 | 76 | 0.4248 | |
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| 0.3828 | 9.62 | 77 | 0.4244 | |
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| 0.384 | 9.75 | 78 | 0.4241 | |
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| 0.3985 | 9.88 | 79 | 0.4239 | |
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| 0.4912 | 10.0 | 80 | 0.4238 | |
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### Framework versions |
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- Transformers 4.28.1 |
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- Pytorch 2.0.0+cu118 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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