rvind2508/codellama-7b-learning_rate2e-4

1---2library_name: peft3license: llama24base_model: codellama/CodeLlama-7b-hf5tags:6- base_model:adapter:codellama/CodeLlama-7b-hf7- lora8- transformers9pipeline_tag: text-generation10model-index:11- name: codellama-7b-learning_rate2e-412  results: []13---14 15<!-- This model card has been generated automatically according to the information the Trainer had access to. You16should probably proofread and complete it, then remove this comment. -->17 18# codellama-7b-learning_rate2e-419 20This model is a fine-tuned version of [codellama/CodeLlama-7b-hf](https://huggingface.co/codellama/CodeLlama-7b-hf) on an unknown dataset.21It achieves the following results on the evaluation set:22- Loss: 1.227023 24## Model description25 26More information needed27 28## Intended uses & limitations29 30More information needed31 32## Training and evaluation data33 34More information needed35 36## Training procedure37 38### Training hyperparameters39 40The following hyperparameters were used during training:41- learning_rate: 0.000242- train_batch_size: 143- eval_batch_size: 144- seed: 4245- gradient_accumulation_steps: 3246- total_train_batch_size: 3247- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments48- lr_scheduler_type: cosine49- lr_scheduler_warmup_steps: 0.0550- training_steps: 10051 52### Training results53 54| Training Loss | Epoch | Step | Validation Loss |55|:-------------:|:-----:|:----:|:---------------:|56| 1.1488        | 1.0   | 100  | 1.2270          |57 58 59### Framework versions60 61- PEFT 0.18.162- Transformers 5.3.063- Pytorch 2.5.1+cu12164- Datasets 4.7.065- Tokenizers 0.22.2