---
license: llama2
base_model: h2oai/h2ogpt-16k-codellama-7b-instruct
tags:
- generated_from_trainer
model-index:
- name: h2ogpt-16k-codellama-7b-instruct-finetuned-1-2024-03-06-16
  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. -->

# h2ogpt-16k-codellama-7b-instruct-finetuned-1-2024-03-06-16

This model is a fine-tuned version of [h2oai/h2ogpt-16k-codellama-7b-instruct](https://huggingface.co/h2oai/h2ogpt-16k-codellama-7b-instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0141

## 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: 0.0003
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 64
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.6967        | 1.17  | 20   | 0.4241          |
| 0.2982        | 2.33  | 40   | 0.2148          |
| 0.1461        | 3.5   | 60   | 0.1113          |
| 0.0856        | 4.66  | 80   | 0.0586          |
| 0.0631        | 5.83  | 100  | 0.0419          |
| 0.0577        | 6.99  | 120  | 0.0318          |
| 0.064         | 8.16  | 140  | 0.0464          |
| 0.0444        | 9.33  | 160  | 0.0308          |
| 0.0463        | 10.49 | 180  | 0.0284          |
| 0.0372        | 11.66 | 200  | 0.0276          |
| 0.0345        | 12.82 | 220  | 0.0253          |
| 0.0384        | 13.99 | 240  | 0.0230          |
| 0.0313        | 15.15 | 260  | 0.0201          |
| 0.0246        | 16.32 | 280  | 0.0168          |
| 0.0196        | 17.49 | 300  | 0.0141          |
| 0.0166        | 18.65 | 320  | 0.0140          |
| 0.0146        | 19.82 | 340  | 0.0141          |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.2.1+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2