---
library_name: transformers
license: mit
base_model: nisten/Biggie-SmoLlm-0.15B-Base
tags:
- generated_from_trainer
- function_calling
- function-calling
- GGUF
model-index:
- name: capybara_finetuned_results
  results: []
datasets:
- NousResearch/hermes-function-calling-v1
pipeline_tag: text2text-generation
---

<!-- 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_results

This model is a fine-tuned version of [nisten/Biggie-SmoLlm-0.15B-Base](https://huggingface.co/nisten/Biggie-SmoLlm-0.15B-Base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0289

## Model description

![video](https://0x0.st/XYF7.mp4)
<video controls autoplay muted src="https://0x0.st/XYF7.mp4"></video>
## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 15
- training_steps: 300

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.0284        | 8.4507 | 300  | 0.0289          |


### Framework versions

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