---
license: llama2
library_name: peft
tags:
- llama-factory
- lora
- generated_from_trainer
base_model: Yhyu13/LMCocktail-10.7B-v1
model-index:
- name: LMCocktail-10.7B-v1-sft-glaive-function-calling-v2-ep1-lora
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# LMCocktail-10.7B-v1-sft-glaive-function-calling-v2-ep1-lora

This model is a fine-tuned version of [Yhyu13/LMCocktail-10.7B-v1](https://huggingface.co/Yhyu13/LMCocktail-10.7B-v1) on the https://huggingface.co/datasets/Yhyu13/glaive-function-calling-v2-llama-factory-convert dataset, but with a subset of only the first 2000 data entries.
It achieves the following results on the evaluation set:
- Loss: 0.2787

Training script is availbale at ./scripts/

## 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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- total_eval_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 1.0

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.2696        | 1.0   | 747  | 0.2787          |


### Framework versions

- PEFT 0.7.1
- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0