codellamafinetune / README.md
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---
license: llama2
base_model: codellama/CodeLlama-7b-Instruct-hf
tags:
- generated_from_trainer
model-index:
- name: codellamafinetune
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# codellamafinetune
This model is a fine-tuned version of [codellama/CodeLlama-7b-Instruct-hf](https://huggingface.co/codellama/CodeLlama-7b-Instruct-hf) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.0044
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.688 | 1.0 | 1 | 2.6557 |
| 2.1862 | 2.0 | 2 | 2.0614 |
| 1.6295 | 3.0 | 3 | 1.5751 |
| 1.1295 | 4.0 | 4 | 1.1448 |
| 0.596 | 5.0 | 5 | 0.9583 |
| 0.2845 | 6.0 | 6 | 0.9543 |
| 0.1825 | 7.0 | 7 | 1.0156 |
| 0.1624 | 8.0 | 8 | 1.0044 |
### Framework versions
- Transformers 4.33.0
- Pytorch 2.0.1
- Datasets 2.16.1
- Tokenizers 0.13.3