---
library_name: transformers
base_model: mrcuddle/NemoMix-Magcap-12B
tags:
- axolotl
- generated_from_trainer
datasets:
- mrcuddle/adonis_nsfw_alpaca
model-index:
- name: Magcap-Adonis-12B
  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: `0.12.0.dev0`
```yaml
base_model: mrcuddle/NemoMix-Magcap-12B
tokenizer_type: AutoTokenizer
hub_model_id: mrcuddle/Magcap-Adonis-12B
strict: false

datasets:
  - path: mrcuddle/adonis_nsfw_alpaca
    type: alpaca
    streaming: false

output_dir: ./mistral-12b-adonis


sequence_len: 2048
sample_packing: true
pad_to_sequence_len: true


eval_sample_packing: False
gradient_accumulation_steps: 2
micro_batch_size: 2
num_epochs: 4
optimizer: paged_adamw_8bit
lr_scheduler: cosine
learning_rate: 0.00005

train_on_inputs: false
group_by_length: false

bf16: auto
fp16:
past_model_outputs: false

gradient_checkpointing: true
save_steps: 500
special_tokens:
  bos_token: "<s>"
  eos_token: "</s>"
  pad_token: "</s>"
```

</details><br>

# Magcap-Adonis-12B

This model is a fine-tuned version of [mrcuddle/NemoMix-Magcap-12B](https://huggingface.co/mrcuddle/NemoMix-Magcap-12B) on the mrcuddle/adonis_nsfw_alpaca 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: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- 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
- training_steps: 32

### Training results



### Framework versions

- Transformers 4.53.2
- Pytorch 2.7.1+cu126
- Datasets 4.0.0
- Tokenizers 0.21.2