---
license: other
library_name: peft
tags:
- llama-factory
- lora
- unsloth
- generated_from_trainer
base_model: cognitivecomputations/dolphin-2.9-llama3-8b
model-index:
- name: dolphin-2.9-llama3-8b-GER
  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-2.9-llama3-8b-GER

This model is a fine-tuned version of [cognitivecomputations/dolphin-2.9-llama3-8b](https://huggingface.co/cognitivecomputations/dolphin-2.9-llama3-8b) on the identity, the alpaca-gpt4_de, the dolphin_de and the airoboros_de datasets.
It achieves the following results on the evaluation set:
- Loss: 0.9384

## 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: 0.0002
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- total_eval_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- lr_scheduler_warmup_steps: 80
- num_epochs: 1.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.2054        | 0.12  | 100  | 1.0369          |
| 1.0667        | 0.24  | 200  | 1.0012          |
| 1.0751        | 0.35  | 300  | 0.9849          |
| 0.8838        | 0.47  | 400  | 0.9696          |
| 0.9846        | 0.59  | 500  | 0.9565          |
| 0.9523        | 0.71  | 600  | 0.9486          |
| 0.8567        | 0.82  | 700  | 0.9430          |
| 0.8284        | 0.94  | 800  | 0.9384          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 2.16.0
- Tokenizers 0.15.2