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---
tags:
- generated_from_trainer
model-index:
- name: vicuna-adv-robust-u50-sft-lora
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. -->
# vicuna-adv-robust-u50-sft-lora
This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2125
## 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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 16
- total_train_batch_size: 512
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 50
### Training results
| 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 |
### Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0a0+32f93b1
- Datasets 2.14.6
- Tokenizers 0.14.1
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