---
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