tensorboard safetensors generated_from_trainer region:us
---
tags:
- generated_from_trainer
model-index:
- name: vicuna-adv-robust-u20-sft-lora
  results: []
---

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# vicuna-adv-robust-u20-sft-lora

This model was trained from scratch on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2191

## 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: 3e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 16
- total_train_batch_size: 256
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 2.5536        | 0.12  | 1    | 2.4988          |
| 2.5536        | 1.1   | 2    | 2.5688          |
| 2.5536        | 2.08  | 3    | 2.5704          |
| 2.5536        | 3.05  | 4    | 2.6317          |
| 2.5982        | 4.03  | 5    | 2.5004          |
| 2.5982        | 5.13  | 7    | 2.5414          |
| 2.5982        | 6.11  | 8    | 2.4437          |
| 2.5982        | 7.08  | 9    | 2.4887          |
| 2.5575        | 8.06  | 10   | 2.5658          |
| 2.5575        | 9.04  | 11   | 2.5603          |
| 2.5575        | 10.14 | 13   | 2.4061          |
| 2.5575        | 11.11 | 14   | 2.4262          |
| 2.5037        | 12.09 | 15   | 2.4319          |
| 2.5037        | 13.07 | 16   | 2.3978          |
| 2.5037        | 14.05 | 17   | 2.3657          |
| 2.5037        | 15.14 | 19   | 2.3580          |
| 2.4117        | 16.12 | 20   | 2.3231          |
| 2.4117        | 17.1  | 21   | 2.3328          |
| 2.4117        | 18.08 | 22   | 2.3051          |
| 2.4117        | 19.05 | 23   | 2.2653          |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0a0+32f93b1
- Datasets 2.14.6
- Tokenizers 0.14.1
