Downloads · 30 days
0
justinwangx/vicuna-adv-robust-u50-sft-lora
vicuna-adv-robust-u50-sft-lora is a machine learning model from justinwangx. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
should probably proofread and complete it, then remove this comment. --
Downloads · 30 days
0
Access
Public
Updated Jan 1, 2024
Repo size
135 MB
Likes
0
Public
Click a slice to open those files.
.safetensors134 MB · 98%
From the Hugging Face model README
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
More information needed
More information needed
More information needed
The following hyperparameters were used during training:
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 0 | 0 | 2.4952 |
| 2.5615 | 1.09 | 1 | 2.5270 |
| 2.5615 | 1.09 | 1 | 2.5362 |
| 2.5615 | 3.03 | 2 | 2.5342 |
| 2.5615 | 4.12 | 3 | 2.2735 |
| 2.5615 | 4.12 | 3 | 2.3209 |
| 2.5615 | 6.06 | 4 | 2.1017 |
| 2.363 | 7.15 | 5 | 2.0121 |
| 2.363 | 7.15 | 5 | 2.0751 |
| 2.363 | 9.09 | 6 | 1.9646 |
| 2.363 | 9.09 | 6 | 1.8912 |
| 2.363 | 11.03 | 7 | 1.8100 |
| 2.363 | 12.12 | 8 | 1.8144 |
| 2.363 | 12.12 | 8 | 1.7983 |
| 2.363 | 14.06 | 9 | 1.7634 |
| 1.9009 | 15.15 | 10 | 1.7628 |
| 1.9009 | 15.15 | 10 | 1.7354 |
| 1.9009 | 17.09 | 11 | 1.7343 |
| 1.9009 | 17.09 | 11 | 1.7232 |
| 1.9009 | 19.03 | 12 | 1.6737 |
| 1.9009 | 20.12 | 13 | 1.6418 |
| 1.9009 | 20.12 | 13 | 1.6635 |
| 1.9009 | 22.06 | 14 | 1.6280 |
| 1.7031 | 23.15 | 15 | 1.6042 |
| 1.7031 | 23.15 | 15 | 1.6120 |
| 1.7031 | 25.09 | 16 | 1.5792 |
| 1.7031 | 25.09 | 16 | 1.6128 |
| 1.7031 | 27.03 | 17 | 1.5468 |
| 1.7031 | 28.12 | 18 | 1.5303 |
| 1.7031 | 28.12 | 18 | 1.5160 |
| 1.7031 | 30.06 | 19 | 1.5195 |
| 1.5968 | 31.15 | 20 | 1.5098 |
| 1.5968 | 31.15 | 20 | 1.4775 |
| 1.5968 | 33.09 | 21 | 1.4770 |
| 1.5968 | 33.09 | 21 | 1.4588 |
| 1.5968 | 35.03 | 22 | 1.4474 |
| 1.5968 | 36.12 | 23 | 1.4240 |
| 1.5968 | 36.12 | 23 | 1.4164 |
| 1.5968 | 38.06 | 24 | 1.4060 |
| 1.4776 | 39.15 | 25 | 1.3753 |
| 1.4776 | 39.15 | 25 | 1.3858 |
| 1.4776 | 41.09 | 26 | 1.3822 |
| 1.4776 | 41.09 | 26 | 1.3268 |
| 1.4776 | 43.03 | 27 | 1.3443 |
| 1.4776 | 44.12 | 28 | 1.3259 |
| 1.4776 | 44.12 | 28 | 1.3117 |
| 1.4776 | 46.06 | 29 | 1.3105 |
| 1.3585 | 47.15 | 30 | 1.2553 |
| 1.3585 | 47.15 | 30 | 1.2755 |
| 1.3585 | 49.09 | 31 | 1.2036 |