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---
base_model: teknium/OpenHermes-2.5-Mistral-7B
library_name: peft
license: apache-2.0
pipeline_tag: text2text-generation
tags:
- generated_from_trainer
model-index:
- name: open-hermes-erotic-story-finetune
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/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/timur-yarullov-tune/erotic-story-finetune/runs/wjag882u)
# open-hermes-erotic-story-finetune
This model is a fine-tuned version of [teknium/OpenHermes-2.5-Mistral-7B](https://huggingface.co/teknium/OpenHermes-2.5-Mistral-7B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1465
## 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-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- training_steps: 1500
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.1158 | 0.1056 | 50 | 0.2470 |
| 0.2078 | 0.2112 | 100 | 0.1934 |
| 0.1866 | 0.3168 | 150 | 0.1867 |
| 0.1804 | 0.4224 | 200 | 0.1719 |
| 0.158 | 0.5280 | 250 | 0.1515 |
| 0.15 | 0.6336 | 300 | 0.1507 |
| 0.1489 | 0.7392 | 350 | 0.1499 |
| 0.1464 | 0.8448 | 400 | 0.1494 |
| 0.1485 | 0.9504 | 450 | 0.1487 |
| 0.1485 | 1.0560 | 500 | 0.1485 |
| 0.1459 | 1.1616 | 550 | 0.1484 |
| 0.1444 | 1.2672 | 600 | 0.1481 |
| 0.1469 | 1.3728 | 650 | 0.1477 |
| 0.148 | 1.4784 | 700 | 0.1477 |
| 0.1438 | 1.5839 | 750 | 0.1475 |
| 0.1454 | 1.6895 | 800 | 0.1472 |
| 0.149 | 1.7951 | 850 | 0.1471 |
| 0.1395 | 1.9007 | 900 | 0.1469 |
| 0.1416 | 2.0063 | 950 | 0.1468 |
| 0.1443 | 2.1119 | 1000 | 0.1468 |
| 0.1445 | 2.2175 | 1050 | 0.1467 |
| 0.143 | 2.3231 | 1100 | 0.1468 |
| 0.1416 | 2.4287 | 1150 | 0.1468 |
| 0.1418 | 2.5343 | 1200 | 0.1466 |
| 0.1384 | 2.6399 | 1250 | 0.1466 |
| 0.1382 | 2.7455 | 1300 | 0.1466 |
| 0.1423 | 2.8511 | 1350 | 0.1466 |
| 0.1414 | 2.9567 | 1400 | 0.1465 |
| 0.1398 | 3.0623 | 1450 | 0.1465 |
| 0.136 | 3.1679 | 1500 | 0.1465 |
### Framework versions
- PEFT 0.11.2.dev0
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |