tensorboard safetensors generated_from_trainer base_model:codellama/CodeLlama-13b-Instruct-hf base_model:finetune:codellama/CodeLlama-13b-Instruct-hf license:llama2 region:us
---
base_model: codellama/CodeLlama-13b-Instruct-hf
license: llama2
metrics:
- accuracy
- bleu
- sacrebleu
- rouge
tags:
- generated_from_trainer
model-index:
- name: CodeLlama-13b-Instruct-hf_En__translations_size_104_epochs_10_2024-06-22_07-00-27_3558000
  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. -->

# CodeLlama-13b-Instruct-hf_En__translations_size_104_epochs_10_2024-06-22_07-00-27_3558000

This model is a fine-tuned version of [codellama/CodeLlama-13b-Instruct-hf](https://huggingface.co/codellama/CodeLlama-13b-Instruct-hf) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7291
- Accuracy: 0.053
- Chrf: 0.654
- Bleu: 0.554
- Sacrebleu: 0.6
- Rouge1: 0.61
- Rouge2: 0.367
- Rougel: 0.556
- Rougelsum: 0.603
- Meteor: 0.542

## 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: 104
- training_steps: 1040

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Chrf  | Bleu  | Sacrebleu | Rouge1 | Rouge2 | Rougel | Rougelsum | Meteor |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----:|:-----:|:---------:|:------:|:------:|:------:|:---------:|:------:|
| 0.2903        | 4.0   | 104  | 2.0336          | 0.052    | 0.541 | 0.417 | 0.4       | 0.524  | 0.268  | 0.48   | 0.519     | 0.477  |
| 0.2305        | 8.0   | 208  | 2.2999          | 0.05     | 0.513 | 0.412 | 0.4       | 0.495  | 0.26   | 0.454  | 0.489     | 0.453  |
| 0.1581        | 12.0  | 312  | 2.0944          | 0.054    | 0.566 | 0.475 | 0.5       | 0.548  | 0.313  | 0.502  | 0.543     | 0.52   |
| 0.6402        | 16.0  | 416  | 1.9048          | 0.05     | 0.601 | 0.482 | 0.5       | 0.568  | 0.32   | 0.521  | 0.562     | 0.544  |
| 0.1487        | 20.0  | 520  | 2.0162          | 0.054    | 0.591 | 0.487 | 0.5       | 0.567  | 0.324  | 0.516  | 0.556     | 0.472  |
| 0.1857        | 24.0  | 624  | 2.0241          | 0.055    | 0.572 | 0.481 | 0.5       | 0.545  | 0.304  | 0.499  | 0.542     | 0.509  |
| 0.718         | 28.0  | 728  | 1.7555          | 0.054    | 0.63  | 0.529 | 0.5       | 0.595  | 0.345  | 0.549  | 0.588     | 0.532  |
| 0.1329        | 32.0  | 832  | 1.7785          | 0.053    | 0.651 | 0.554 | 0.6       | 0.619  | 0.379  | 0.567  | 0.614     | 0.536  |
| 0.2488        | 36.0  | 936  | 1.7203          | 0.052    | 0.657 | 0.556 | 0.6       | 0.608  | 0.371  | 0.558  | 0.599     | 0.549  |
| 0.1337        | 40.0  | 1040 | 1.7291          | 0.053    | 0.654 | 0.554 | 0.6       | 0.61   | 0.367  | 0.556  | 0.603     | 0.542  |


### Framework versions

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