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---
tags:
- generated_from_trainer
model-index:
- name: lora-out5
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. -->
[<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)
# lora-out5
This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1214
## 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: 2.5e-07
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_steps: 10
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.8362 | 0.03 | 1 | 1.7488 |
| 2.035 | 2.46 | 80 | 1.6462 |
| 1.5489 | 4.92 | 160 | 1.4901 |
| 1.4392 | 7.38 | 240 | 1.3567 |
| 1.2196 | 9.85 | 320 | 1.2475 |
| 1.3219 | 12.31 | 400 | 1.2089 |
| 1.2171 | 14.77 | 480 | 1.1870 |
| 1.1686 | 17.23 | 560 | 1.1730 |
| 1.1506 | 19.69 | 640 | 1.1615 |
| 1.1829 | 22.15 | 720 | 1.1513 |
| 1.267 | 24.62 | 800 | 1.1454 |
| 1.0857 | 27.08 | 880 | 1.1367 |
| 1.0795 | 29.54 | 960 | 1.1345 |
| 1.0453 | 32.0 | 1040 | 1.1317 |
| 1.2093 | 34.46 | 1120 | 1.1283 |
| 1.1442 | 36.92 | 1200 | 1.1253 |
| 0.966 | 39.38 | 1280 | 1.1239 |
| 0.9576 | 41.85 | 1360 | 1.1227 |
| 1.0146 | 44.31 | 1440 | 1.1222 |
| 1.0243 | 46.77 | 1520 | 1.1213 |
| 1.0192 | 49.23 | 1600 | 1.1214 |
### Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.7
- Tokenizers 0.15.0
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