---
library_name: transformers
license: apache-2.0
base_model: Qwen/Qwen2.5-0.5B
tags:
- generated_from_trainer
- qwen
- GGUF
- worldmodel
- worldbuilding
model-index:
- name: capybara_finetuned_results3
  results: []
datasets:
- archit11/worldbuilding
---

<!-- 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. -->

# capybara_finetuned_results3

This model is a fine-tuned version of [Qwen/Qwen2.5-0.5B](https://huggingface.co/Qwen/Qwen2.5-0.5B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 5.6542

## video demo : (its pretty bad)

<video controls autoplay muted src="https://0x0.st/XgZs.mp4"></video>

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: 0.0002
- train_batch_size: 1
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 5
- training_steps: 800

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 15.5311       | 0.0230 | 50   | 14.5422         |
| 8.7477        | 0.0460 | 100  | 9.2952          |
| 7.3554        | 0.0690 | 150  | 7.1992          |
| 6.828         | 0.0920 | 200  | 6.7258          |
| 6.4694        | 0.1150 | 250  | 6.3597          |
| 6.3401        | 0.1381 | 300  | 6.1703          |
| 6.1256        | 0.1611 | 350  | 6.0395          |
| 6.0372        | 0.1841 | 400  | 5.9271          |
| 6.0221        | 0.2071 | 450  | 5.8464          |
| 5.8783        | 0.2301 | 500  | 5.7810          |
| 5.8339        | 0.2531 | 550  | 5.7335          |
| 5.8546        | 0.2761 | 600  | 5.6904          |
| 5.9169        | 0.2991 | 650  | 5.6690          |
| 5.7959        | 0.3221 | 700  | 5.6565          |
| 5.7271        | 0.3451 | 750  | 5.6543          |
| 5.8734        | 0.3682 | 800  | 5.6542          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0
- Datasets 3.0.0
- Tokenizers 0.19.1