---
license: apache-2.0
library_name: peft
tags:
- llama-factory
- lora
- generated_from_trainer
base_model: cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser
model-index:
- name: dolphin-2.6-mistral-7b-dpo-laser-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
should probably proofread and complete it, then remove this comment. -->

# dolphin-2.6-mistral-7b-dpo-laser-sft-glaive-function-calling-v2-ep1-lora

This model is a fine-tuned version of [cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser](https://huggingface.co/cognitivecomputations/dolphin-2.6-mistral-7b-dpo-laser) on the https://huggingface.co/datasets/Yhyu13/glaive-function-calling-v2-llama-factory-convert/blob/main/simple-function-calling-v2_converted_5000_with_function_call_only.json dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0605

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 0.2548        | 0.09  | 100  | 0.1148          |
| 0.1149        | 0.18  | 200  | 0.0914          |
| 0.0871        | 0.27  | 300  | 0.0831          |
| 0.0865        | 0.35  | 400  | 0.0760          |
| 0.0802        | 0.44  | 500  | 0.0718          |
| 0.0689        | 0.53  | 600  | 0.0702          |
| 0.0649        | 0.62  | 700  | 0.0649          |
| 0.0637        | 0.71  | 800  | 0.0632          |
| 0.0698        | 0.8   | 900  | 0.0619          |
| 0.0648        | 0.88  | 1000 | 0.0608          |
| 0.0654        | 0.97  | 1100 | 0.0605          |


### Framework versions

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