---
library_name: transformers
license: other
base_model: mrcuddle/tiny-darkllama
tags:
- generated_from_trainer
datasets:
- Nitral-AI/Reddit-NSFW-Writing_Prompts_ShareGPT
model-index:
- name: model-out
  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: `0.6.0`
```yaml
base_model: mrcuddle/tiny-darkllama
bf16: auto
datasets:
- chat_template: tokenizer_default
  field_messages: conversations
  message_field_content: value
  message_field_role: from
  path: Nitral-AI/Reddit-NSFW-Writing_Prompts_ShareGPT
  split: train
  type: chat_template
debug: null
deepspeed: null
early_stopping_patience: null
eval_sample_packing: true
eval_table_size: null
evals_per_epoch: 1
flash_attention: false
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 2
gradient_checkpointing: true
group_by_length: false
learning_rate: 2e-5
load_in_4bit: false
load_in_8bit: false
logging_steps: 1
lr_scheduler: cosine
max_steps: 25
micro_batch_size: 1
num_epochs: 1
optimizer: paged_adamw_8bit
pad_to_sequence_len: true
resume_from_checkpoint: null
sample_packing: true
saves_per_epoch: 1
sdp_attention: true
sequence_len: 2048
special_tokens:
  pad_token: <|end_of_text|>
strict: false
tf32: false
train_on_inputs: false
warmup_steps: 1
weight_decay: 0.0
xformers_attention: null

```

</details><br>

# model-out

This model is a fine-tuned version of [mrcuddle/tiny-darkllama](https://huggingface.co/mrcuddle/tiny-darkllama) on the Nitral-AI/Reddit-NSFW-Writing_Prompts_ShareGPT 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: 2e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- total_eval_batch_size: 2
- optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT 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
- training_steps: 25

### Training results



### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.21.0