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--- |
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license: llama2 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- AshtonIsNotHere/nlp_pp_code_dataset |
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metrics: |
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- accuracy |
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model-index: |
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- name: CodeLlama_7B_nlp_pp |
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results: |
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- task: |
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name: Causal Language Modeling |
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type: text-generation |
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dataset: |
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name: AshtonIsNotHere/nlp_pp_code_dataset |
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type: AshtonIsNotHere/nlp_pp_code_dataset |
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split: test |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8968056729128353 |
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--- |
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# CodeLlama_7B_nlp_pp |
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This model is a fine-tuned version of [codellama/CodeLlama-7b-hf](https://huggingface.co/codellama/CodeLlama-7b-hf) on the AshtonIsNotHere/nlp_pp_code_dataset dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4129 |
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- Accuracy: 0.8968 |
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## Model description |
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This model has been fine-tuned for code completion on a dataset of NLP++ code. |
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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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Dataset consists of a combination of scraped NLP++ code and NLP++ code examples from the [VisualText website](https://visualtext.org/help/). |
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## Training procedure |
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This model is trained in a multinode, multi-gpu setup with DeepSpeed Z3. For more information on the training setup, check out the [GitHub repo](https://github.com/ashtonomy/nlp_pp_code_completion). |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.00012 |
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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: 4 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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- total_eval_batch_size: 4 |
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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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- lr_scheduler_warmup_ratio: 0.1 |
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- num_epochs: 7.0 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| No log | 1.0 | 61 | 0.5100 | 0.8726 | |
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| No log | 1.99 | 122 | 0.4129 | 0.8968 | |
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| No log | 2.99 | 183 | 0.4166 | 0.9072 | |
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| No log | 4.0 | 245 | 0.4595 | 0.9090 | |
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| No log | 5.0 | 306 | 0.5181 | 0.9093 | |
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| No log | 5.99 | 367 | 0.5553 | 0.9090 | |
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| No log | 6.97 | 427 | 0.5603 | 0.9089 | |
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### Framework versions |
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- Transformers 4.30.2 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.13.0 |
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- Tokenizers 0.13.3 |
