metadata
license: other
base_model: microsoft/Orca-2-13b
tags:
- generated_from_trainer
model-index:
- name: Orca-2-13B-Pygmalion-LoRA
results: []
datasets:
- PygmalionAI/PIPPA
language:
- en
++ This model's response was too short, so I re-trained it, check this out: https://huggingface.co/ricecake/Orca-2-13B-Pyg-and-Bluemoon
Orca-2-13B-Pygmalion-LoRA
This LoRA adapter is a fine-tuned version of microsoft/Orca-2-13b on the PygmalionAI/PIPPA dataset. It achieves the following results on the evaluation set:
- Loss: 1.9190
Model description
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 2
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 1
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0.0 | 1 | 3.2585 |
| 1.9811 | 0.05 | 536 | 2.0113 |
| 1.9507 | 0.1 | 1072 | 1.9877 |
| 1.9576 | 0.15 | 1608 | 1.9766 |
| 1.9308 | 0.2 | 2144 | 1.9671 |
| 1.9193 | 0.25 | 2680 | 1.9597 |
| 1.8522 | 0.3 | 3216 | 1.9530 |
| 1.895 | 0.35 | 3752 | 1.9483 |
| 1.869 | 0.4 | 4288 | 1.9432 |
| 1.8664 | 0.45 | 4824 | 1.9383 |
| 1.8661 | 0.5 | 5360 | 1.9347 |
| 1.8576 | 0.55 | 5896 | 1.9337 |
| 1.8573 | 0.6 | 6432 | 1.9286 |
| 1.8665 | 0.65 | 6968 | 1.9280 |
| 1.8429 | 0.7 | 7504 | 1.9243 |
| 1.8621 | 0.75 | 8040 | 1.9221 |
| 1.8074 | 0.8 | 8576 | 1.9209 |
| 1.8199 | 0.85 | 9112 | 1.9202 |
| 1.8733 | 0.9 | 9648 | 1.9193 |
| 1.8387 | 0.95 | 10184 | 1.9190 |
Framework versions
- Transformers 4.35.1
- Pytorch 2.1.0+cu121
- Datasets 2.14.7
- Tokenizers 0.14.1