|
--- |
|
license: cc-by-nc-4.0 |
|
base_model: athirdpath/BigMistral-11b |
|
tags: |
|
- generated_from_trainer |
|
model-index: |
|
- name: qlora |
|
results: [] |
|
language: |
|
- en |
|
pipeline_tag: text-generation |
|
--- |
|
|
|
[<img src="https://raw.githubusercontent.com/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl) |
|
|
|
<p align="center"><font size="5"> <b>Regret: Should have not targeted Q, V, K, O; as those are less impactful for "healing" but more impactful on performance otherwise. Still works great!</b> </font></p> |
|
|
|
# qlora |
|
|
|
This model is a fine-tuned version of [athirdpath/BigMistral-11b](https://huggingface.co/athirdpath/BigMistral-11b) on the athirdpath/Merge_Glue dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.9174 |
|
|
|
<p align="center"><font size="7"> <b>Before and After Example</b></font></p> |
|
<p align="center"><font size="4"> <b>Example model is athirdpath/CleverMage-11b</b></font></p> |
|
<p align="center"><font size="5"> <b>Example with LoRA (min_p, alpaca)</b></font></p> |
|
<p align="center"><img src="https://iili.io/JzsmqzJ.png"/> |
|
<p align="center"><font size="5"> <b>Example without LoRA (min_p, chatML)</b></font></p> |
|
<p align="center"><img src="https://iili.io/JzsmCsR.png"/> |
|
|
|
### Training hyperparameters |
|
|
|
The following hyperparameters were used during training: |
|
- learning_rate: 0.0005 |
|
- train_batch_size: 10 |
|
- eval_batch_size: 10 |
|
- seed: 42 |
|
- gradient_accumulation_steps: 4 |
|
- total_train_batch_size: 40 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: cosine |
|
- lr_scheduler_warmup_steps: 10 |
|
- num_epochs: 3 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:-----:|:----:|:---------------:| |
|
| 1.2198 | 0.63 | 30 | 0.9055 | |
|
| 1.1206 | 1.26 | 60 | 0.8951 | |
|
| 1.1319 | 1.89 | 90 | 0.8904 | |
|
| 1.0031 | 2.51 | 120 | 0.9174 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.35.2 |
|
- Pytorch 2.0.1+cu118 |
|
- Datasets 2.15.0 |
|
- Tokenizers 0.15.0 |
|
|
