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distilgpt2_fine_tuned_gcode

Text Generation
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gpt2
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june

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  1. README.md +1 -55
  2. pytorch_model.bin +1 -1
  3. runs/Jun10_18-26-32_hal10/1654904530.7637877/events.out.tfevents.1654904530.hal10.596337.1 +0 -3
  4. runs/Jun10_18-26-32_hal10/events.out.tfevents.1654904530.hal10.596337.0 +0 -3
  5. runs/Jun10_20-14-03_hal01/1654910111.593988/events.out.tfevents.1654910111.hal01.3050200.1 +0 -3
  6. runs/Jun10_20-14-03_hal01/events.out.tfevents.1654910111.hal01.3050200.0 +0 -3
  7. runs/Jun10_20-14-03_hal01/events.out.tfevents.1654918283.hal01.3050200.2 +0 -3
  8. runs/May13_16-56-59_hal11/events.out.tfevents.1652479135.hal11.132641.0 +2 -2
  9. runs/May13_16-56-59_hal11/events.out.tfevents.1652483113.hal11.132641.2 +0 -3
  10. training_args.bin +1 -1
README.md CHANGED
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- ---
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- tags:
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- - generated_from_trainer
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- model-index:
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- - name: distilgpt2_fine_tuned_gcode
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- results: []
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- ---
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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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-
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- # distilgpt2_fine_tuned_gcode
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-
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- This model is a fine-tuned version of [congcongwang/distilgpt2_fine_tuned_coder](https://huggingface.co/congcongwang/distilgpt2_fine_tuned_coder) on the None dataset.
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- It achieves the following results on the evaluation set:
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- - Loss: 4.1670
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-
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- ## Model description
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-
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- More information needed
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-
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- ## Intended uses & limitations
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-
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- More information needed
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-
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- ## Training and evaluation data
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-
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- More information needed
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-
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- ## Training procedure
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-
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- ### Training hyperparameters
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-
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- The following hyperparameters were used during training:
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- - learning_rate: 0.1
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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: 1
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-
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- ### Training results
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-
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- | Training Loss | Epoch | Step | Validation Loss |
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- |:-------------:|:-----:|:-----:|:---------------:|
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- | 4.1754 | 1.0 | 52144 | 4.1670 |
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-
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-
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- ### Framework versions
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-
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- - Transformers 4.15.0
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- - Pytorch 1.10.1
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- - Datasets 2.1.0
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- - Tokenizers 0.10.3
 
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+ Sample generation of Gcode via finetuned code. Work in progress.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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