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---
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
should probably proofread and complete it, then remove this comment. -->
# 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 |