---
license: llama2
library_name: peft
tags:
- generated_from_trainer
base_model: codellama/CodeLlama-7b-Instruct-hf
metrics:
- accuracy
- bleu
- sacrebleu
- rouge
model-index:
- name: CodeLlama-7b-Instruct-hf_Fi__CMP_TR_size_304_epochs_10_2024-06-22_21-11-23_3558625
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# CodeLlama-7b-Instruct-hf_Fi__CMP_TR_size_304_epochs_10_2024-06-22_21-11-23_3558625

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: 1.9442
- Accuracy: 0.464
- Chrf: 0.282
- Bleu: 0.212
- Sacrebleu: 0.2
- Rouge1: 0.473
- Rouge2: 0.304
- Rougel: 0.447
- Rougelsum: 0.467
- Meteor: 0.474

## 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: 1
- eval_batch_size: 1
- seed: 3407
- distributed_type: multi-GPU
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 304
- training_steps: 3040

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Chrf  | Bleu  | Sacrebleu | Rouge1 | Rouge2 | Rougel | Rougelsum | Meteor |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:|:-----:|:---------:|:------:|:------:|:------:|:---------:|:------:|
| 0.7293        | 1.0   | 304  | 2.8400          | 0.471    | 0.109 | 0.089 | 0.1       | 0.318  | 0.168  | 0.304  | 0.297     | 0.274  |
| 0.043         | 2.0   | 608  | 3.2408          | 0.498    | 0.051 | 0.019 | 0.0       | 0.162  | 0.063  | 0.136  | 0.142     | 0.216  |
| 0.0514        | 3.0   | 912  | 2.8322          | 0.478    | 0.156 | 0.059 | 0.1       | 0.3    | 0.145  | 0.284  | 0.289     | 0.289  |
| 0.0145        | 4.0   | 1216 | 2.5898          | 0.478    | 0.101 | 0.064 | 0.1       | 0.263  | 0.167  | 0.258  | 0.258     | 0.32   |
| 0.8203        | 5.0   | 1520 | 2.7395          | 0.478    | 0.16  | 0.049 | 0.0       | 0.306  | 0.114  | 0.284  | 0.298     | 0.27   |
| 0.0546        | 6.0   | 1824 | 2.8379          | 0.458    | 0.052 | 0.022 | 0.0       | 0.068  | 0.0    | 0.056  | 0.057     | 0.21   |
| 0.0352        | 7.0   | 2128 | 2.6987          | 0.481    | 0.165 | 0.133 | 0.1       | 0.356  | 0.246  | 0.352  | 0.355     | 0.33   |
| 0.042         | 8.0   | 2432 | 2.0781          | 0.481    | 0.264 | 0.169 | 0.2       | 0.421  | 0.261  | 0.403  | 0.421     | 0.431  |
| 0.0124        | 9.0   | 2736 | 1.9029          | 0.464    | 0.293 | 0.222 | 0.2       | 0.466  | 0.304  | 0.445  | 0.465     | 0.473  |
| 0.0382        | 10.0  | 3040 | 1.9442          | 0.464    | 0.282 | 0.212 | 0.2       | 0.473  | 0.304  | 0.447  | 0.467     | 0.474  |


### Framework versions

- PEFT 0.7.1
- Transformers 4.37.0
- Pytorch 2.2.1+cu121
- Datasets 2.20.0
- Tokenizers 0.15.2