Create README.md

README.md

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+---
+license: llama2
+base_model: codellama/CodeLlama-7b-hf
+tags:
+- generated_from_trainer
+model-index:
+- name: codellama2-finetuned-codex-py
+  results: []
+datasets:
+- iamtarun/python_code_instructions_18k_alpaca
+language:
+- en
+library_name: peft
+pipeline_tag: text-generation
+---
+
+
+
+# codellama2-finetuned-codex-py
+
+This model is a fine-tuned version of [codellama/CodeLlama-7b-hf](https://huggingface.co/codellama/CodeLlama-7b-hf) on the None dataset.
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+| Step | Training Loss |
+|------|---------------|
+| 10   | 0.792200      |
+| 20   | 0.416100      |
+| 30   | 0.348600      |
+| 40   | 0.323200      |
+| 50   | 0.316300      |
+| 60   | 0.317500      |
+| 70   | 0.333600      |
+| 80   | 0.329500      |
+| 90   | 0.333400      |
+| 100  | 0.309900      |
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 0.0002
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- training_steps: 100
+- mixed_precision_training: Native AMP
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.36.0.dev0
+- Pytorch 2.0.0
+- Datasets 2.1.0
+- Tokenizers 0.15.0