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Model: AshtonIsNotHere/CodeLlama_7B_nlp_pp
Source: Original Platform

README.md

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+---
+license: llama2
+tags:
+- generated_from_trainer
+datasets:
+- AshtonIsNotHere/nlp_pp_code_dataset
+metrics:
+- accuracy
+model-index:
+- name: CodeLlama_7B_nlp_pp
+  results:
+  - task:
+      name: Causal Language Modeling
+      type: text-generation
+    dataset:
+      name: AshtonIsNotHere/nlp_pp_code_dataset
+      type: AshtonIsNotHere/nlp_pp_code_dataset
+      split: test
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8968056729128353
+---
+
+# CodeLlama_7B_nlp_pp
+
+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.
+It achieves the following results on the evaluation set:
+- Loss: 0.4129
+- Accuracy: 0.8968
+
+## Model description
+
+This model has been fine-tuned for code completion on a dataset of NLP++ code. 
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+Dataset consists of a combination of scraped NLP++ code and NLP++ code examples from the [VisualText website](https://visualtext.org/help/).
+
+## Training procedure
+
+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).
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.00012
+- train_batch_size: 1
+- eval_batch_size: 1
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 4
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 16
+- total_eval_batch_size: 4
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 7.0
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 61   | 0.5100          | 0.8726   |
+| No log        | 1.99  | 122  | 0.4129          | 0.8968   |
+| No log        | 2.99  | 183  | 0.4166          | 0.9072   |
+| No log        | 4.0   | 245  | 0.4595          | 0.9090   |
+| No log        | 5.0   | 306  | 0.5181          | 0.9093   |
+| No log        | 5.99  | 367  | 0.5553          | 0.9090   |
+| No log        | 6.97  | 427  | 0.5603          | 0.9089   |
+
+
+### Framework versions
+
+- Transformers 4.30.2
+- Pytorch 2.0.1+cu117
+- Datasets 2.13.0
+- Tokenizers 0.13.3