---
base_model: hiieu/Meta-Llama-3-8B-Instruct-function-calling-json-mode
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: Meta-Llama-3-8B-Instruct-function-calling-json-mode-VisitorRequests
  results: []
library_name: peft
---

<!-- 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. -->

# Meta-Llama-3-8B-Instruct-function-calling-json-mode-VisitorRequests

This model is a fine-tuned version of [hiieu/Meta-Llama-3-8B-Instruct-function-calling-json-mode](https://huggingface.co/hiieu/Meta-Llama-3-8B-Instruct-function-calling-json-mode) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7458

## 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: 8
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- num_epochs: 2

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.0583        | 0.0630 | 1    | 3.3171          |
| 3.2898        | 0.1260 | 2    | 1.8112          |
| 1.7495        | 0.1890 | 3    | 1.3350          |
| 1.3176        | 0.2520 | 4    | 5.6302          |
| 5.9627        | 0.3150 | 5    | 2.1688          |
| 2.1926        | 0.3780 | 6    | 1.4297          |
| 1.3724        | 0.4409 | 7    | 1.2279          |
| 1.2125        | 0.5039 | 8    | 0.9445          |
| 0.9749        | 0.5669 | 9    | 1.1901          |
| 1.2164        | 0.6299 | 10   | 0.9843          |
| 0.9808        | 0.6929 | 11   | 0.9213          |
| 0.8698        | 0.7559 | 12   | 0.8721          |
| 0.8668        | 0.8189 | 13   | 0.9308          |
| 0.8635        | 0.8819 | 14   | 0.8319          |
| 0.7789        | 0.9449 | 15   | 0.8164          |
| 0.7402        | 1.0079 | 16   | 0.8220          |
| 0.7312        | 1.0709 | 17   | 0.8305          |
| 0.7561        | 1.1339 | 18   | 0.9768          |
| 0.9879        | 1.1969 | 19   | 0.8437          |
| 0.7647        | 1.2598 | 20   | 0.8364          |
| 0.7093        | 1.3228 | 21   | 0.8028          |
| 0.7358        | 1.3858 | 22   | 0.8184          |
| 0.7301        | 1.4488 | 23   | 0.8050          |
| 0.7607        | 1.5118 | 24   | 0.7652          |
| 0.6892        | 1.5748 | 25   | 0.7317          |
| 0.7158        | 1.6378 | 26   | 0.7236          |
| 0.6701        | 1.7008 | 27   | 0.7130          |
| 0.6905        | 1.7638 | 28   | 0.7529          |
| 0.6791        | 1.8268 | 29   | 0.7813          |
| 0.7093        | 1.8898 | 30   | 0.7458          |


### Framework versions

- PEFT 0.5.0
- Transformers 4.44.0
- Pytorch 2.1.0+cu118
- Datasets 2.16.0
- Tokenizers 0.19.1