---
license: llama2
base_model: codellama/CodeLlama-7b-Instruct-hf
tags:
- generated_from_trainer
metrics:
- accuracy
- bleu
- sacrebleu
- rouge
model-index:
- name: CodeLlama-7b-Instruct-hf_Fi__components_size_252_epochs_10_2024-06-21_09-35-27_3556547
  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__components_size_252_epochs_10_2024-06-21_09-35-27_3556547

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: 1.9096
- Accuracy: 0.462
- Chrf: 0.297
- Bleu: 0.225
- Sacrebleu: 0.2
- Rouge1: 0.472
- Rouge2: 0.3
- Rougel: 0.459
- Rougelsum: 0.471
- Meteor: 0.505

## 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
- num_devices: 4
- total_train_batch_size: 4
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-06
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 252
- training_steps: 2520

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Chrf  | Bleu  | Sacrebleu | Rouge1 | Rouge2 | Rougel | Rougelsum | Meteor |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:|:-----:|:---------:|:------:|:------:|:------:|:---------:|:------:|
| 0.063         | 4.0   | 252  | 3.6864          | 0.457    | 0.044 | 0.0   | 0.0       | 0.044  | 0.0    | 0.03   | 0.03      | 0.138  |
| 0.0742        | 8.0   | 504  | 2.7260          | 0.474    | 0.104 | 0.036 | 0.0       | 0.148  | 0.009  | 0.126  | 0.143     | 0.24   |
| 0.0774        | 12.0  | 756  | 2.6054          | 0.461    | 0.159 | 0.099 | 0.1       | 0.315  | 0.149  | 0.306  | 0.308     | 0.325  |
| 0.7995        | 16.0  | 1008 | 2.4395          | 0.465    | 0.215 | 0.119 | 0.1       | 0.393  | 0.178  | 0.365  | 0.379     | 0.359  |
| 0.1761        | 20.0  | 1260 | 2.4190          | 0.482    | 0.249 | 0.164 | 0.2       | 0.356  | 0.194  | 0.34   | 0.355     | 0.39   |
| 0.4002        | 24.0  | 1512 | 2.1404          | 0.462    | 0.251 | 0.188 | 0.2       | 0.418  | 0.269  | 0.4    | 0.409     | 0.437  |
| 0.0254        | 28.0  | 1764 | 2.0202          | 0.46     | 0.295 | 0.192 | 0.2       | 0.484  | 0.308  | 0.461  | 0.478     | 0.463  |
| 0.1469        | 32.0  | 2016 | 1.9957          | 0.462    | 0.289 | 0.225 | 0.2       | 0.448  | 0.291  | 0.44   | 0.443     | 0.482  |
| 0.0346        | 36.0  | 2268 | 1.9562          | 0.46     | 0.293 | 0.2   | 0.2       | 0.474  | 0.278  | 0.452  | 0.471     | 0.491  |
| 0.0378        | 40.0  | 2520 | 1.9096          | 0.462    | 0.297 | 0.225 | 0.2       | 0.472  | 0.3    | 0.459  | 0.471     | 0.505  |


### Framework versions

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