---
license: llama3
base_model: Groq/Llama-3-Groq-8B-Tool-Use
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: Groq_Llama-3-Tool-Use-VisitorRequest-Lora
  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. -->

# Groq_Llama-3-Tool-Use-VisitorRequest-Lora

This model is a fine-tuned version of [Groq/Llama-3-Groq-8B-Tool-Use](https://huggingface.co./Groq/Llama-3-Groq-8B-Tool-Use) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6920

## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 2.3852        | 0.0635 | 1    | 5.9455          |
| 5.9202        | 0.1270 | 2    | 2.0524          |
| 2.1422        | 0.1905 | 3    | 1.2710          |
| 1.32          | 0.2540 | 4    | 1.1640          |
| 1.1839        | 0.3175 | 5    | 0.8947          |
| 0.9042        | 0.3810 | 6    | 0.9210          |
| 0.8737        | 0.4444 | 7    | 0.8815          |
| 0.8936        | 0.5079 | 8    | 0.7752          |
| 0.7229        | 0.5714 | 9    | 0.7938          |
| 0.8039        | 0.6349 | 10   | 0.8019          |
| 0.8014        | 0.6984 | 11   | 0.7562          |
| 0.749         | 0.7619 | 12   | 0.7280          |
| 0.71          | 0.8254 | 13   | 0.7346          |
| 0.7461        | 0.8889 | 14   | 0.7208          |
| 0.6635        | 0.9524 | 15   | 0.7096          |
| 0.7271        | 1.0159 | 16   | 0.7038          |
| 0.6691        | 1.0794 | 17   | 0.7117          |
| 0.6672        | 1.1429 | 18   | 0.7996          |
| 0.7766        | 1.2063 | 19   | 0.7333          |
| 0.6818        | 1.2698 | 20   | 0.7651          |
| 0.684         | 1.3333 | 21   | 0.7110          |
| 0.6575        | 1.3968 | 22   | 0.7213          |
| 0.6146        | 1.4603 | 23   | 0.7275          |
| 0.6245        | 1.5238 | 24   | 0.7908          |
| 0.7224        | 1.5873 | 25   | 0.7301          |
| 0.6472        | 1.6508 | 26   | 0.7082          |
| 0.6066        | 1.7143 | 27   | 0.7114          |
| 0.6735        | 1.7778 | 28   | 0.6984          |
| 0.6263        | 1.8413 | 29   | 0.6899          |
| 0.5998        | 1.9048 | 30   | 0.6920          |


### Framework versions

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