---
library_name: transformers
license: gpl-3.0
base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
tags:
- generated_from_trainer
datasets:
- jaydenccc/AI_Storyteller_Dataset
model-index:
- name: models/Tiny_Llama_Storyteller
  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/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
<details><summary>See axolotl config</summary>

axolotl version: `0.9.1.post1`
```yaml
base_model: TinyLlama/TinyLlama-1.1B-Chat-v1.0
batch_size: 4
bf16: auto
datasets:
- path: jaydenccc/AI_Storyteller_Dataset
  type:
    field_instruction: synopsis
    field_output: short_story
    field_system: system
    format: <|user|> {instruction} </s> <|assistant|>
    no_input_format: <|user|> {instruction} </s> <|assistant|>
    system_prompt: ''
learning_rate: 0.0002
logging_steps: 1
micro_batch_size: 2
model_type: LlamaForCausalLM
num_epochs: 4
optimizer: adamw_bnb_8bit
output_dir: ./models/Tiny_Llama_Storyteller
sequence_length: 1024
tf32: false
tokenizer_type: LlamaTokenizer

```

</details><br>

# models/Tiny_Llama_Storyteller

This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-Chat-v1.0](https://huggingface.co/TinyLlama/TinyLlama-1.1B-Chat-v1.0) on the jaydenccc/AI_Storyteller_Dataset dataset.

## 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: 0.0002
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 2
- num_epochs: 4.0

### Training results



### Framework versions

- Transformers 4.51.3
- Pytorch 2.6.0+cu124
- Datasets 3.5.1
- Tokenizers 0.21.1