---
license: llama2
library_name: peft
tags:
- generated_from_trainer
base_model: vilm/vinallama-7b-chat
model-index:
- name: experiments
  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. -->

# experiments

This model is a fine-tuned version of [vilm/vinallama-7b-chat](https://huggingface.co/vilm/vinallama-7b-chat) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4668

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.3854        | 0.7   | 10   | 0.4145          |
| 0.3751        | 1.4   | 20   | 0.3999          |
| 0.3457        | 2.11  | 30   | 0.3857          |
| 0.324         | 2.81  | 40   | 0.3821          |
| 0.2329        | 3.51  | 50   | 0.3845          |
| 0.2332        | 4.21  | 60   | 0.3878          |
| 0.2211        | 4.91  | 70   | 0.3929          |
| 0.1682        | 5.61  | 80   | 0.4093          |
| 0.1503        | 6.32  | 90   | 0.4416          |
| 0.1439        | 7.02  | 100  | 0.4299          |
| 0.1299        | 7.72  | 110  | 0.4648          |
| 0.1074        | 8.42  | 120  | 0.4574          |
| 0.099         | 9.12  | 130  | 0.4655          |
| 0.1078        | 9.82  | 140  | 0.4668          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.36.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.15.2