File size: 1,575 Bytes
7565302 751fa5c 7565302 751fa5c 7565302 751fa5c 7565302 2cf8192 751fa5c 7565302 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 |
---
base_model: huggyllama/llama-7b
library_name: peft
license: mit
tags:
- peft
- lora
- dora
model-index:
- name: llama-3-8-fine-tuned-dora
results: []
datasets:
- timdettmers/openassistant-guanaco
pipeline_tag: text-generation
---
<!-- 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. -->
# llama-3-8-fine-tuned-dora
This model is a fine-tuned version of [huggyllama/llama-7b](https://huggingface.co/huggyllama/llama-7b) on on [openassistant-guanaco](https://huggingface.co/datasets/timdettmers/openassistant-guanaco) dataset.
For LoraConfig we set the `use_dora=True` for the Dora decomposition and comparison with Lora.
## 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: 1
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 1
- mixed_precision_training: Native AMP
### Training results
### Framework versions
- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |