File size: 2,677 Bytes
ee0ba32 e25c56f ee0ba32 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 |
---
license: apache-2.0
base_model: teknium/OpenHermes-2.5-Mistral-7B
tags:
- generated_from_trainer
model-index:
- name: out
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)
# Enhanced Slither Auditor
This model is a fine-tuned version of [teknium/OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1923
## 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: 5e-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- total_eval_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 2
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 1.1498 | 0.0 | 1 | 1.1953 |
| 0.321 | 0.1 | 31 | 0.3176 |
| 0.2693 | 0.2 | 62 | 0.2712 |
| 0.2701 | 0.31 | 93 | 0.2523 |
| 0.27 | 0.41 | 124 | 0.2362 |
| 0.2244 | 0.51 | 155 | 0.2284 |
| 0.2227 | 0.61 | 186 | 0.2260 |
| 0.2167 | 0.71 | 217 | 0.2171 |
| 0.2098 | 0.81 | 248 | 0.2082 |
| 0.1842 | 0.92 | 279 | 0.2047 |
| 0.1917 | 1.02 | 310 | 0.2013 |
| 0.1639 | 1.12 | 341 | 0.1982 |
| 0.1835 | 1.22 | 372 | 0.1968 |
| 0.1666 | 1.32 | 403 | 0.1953 |
| 0.1694 | 1.43 | 434 | 0.1932 |
| 0.1461 | 1.53 | 465 | 0.1929 |
| 0.1535 | 1.63 | 496 | 0.1927 |
| 0.1419 | 1.73 | 527 | 0.1925 |
| 0.1612 | 1.83 | 558 | 0.1923 |
| 0.1857 | 1.93 | 589 | 0.1923 |
### Framework versions
- Transformers 4.34.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
|