---
base_model: tomaszki/nous-twelve
tags:
- axolotl
- generated_from_trainer
model-index:
- name: titos
  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/OpenAccess-AI-Collective/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/OpenAccess-AI-Collective/axolotl)
<details><summary>See axolotl config</summary>

axolotl version: `0.4.0`
```yaml
base_model: tomaszki/nous-twelve
tokenizer_type: AutoTokenizer

hub_model_id: superfriends/titos
load_in_8bit: false
load_in_4bit: false
strict: false

chat_template: inst
datasets:
  - path: winglian/charley
    type: sharegpt
    conversation: mistral
    split: train
_test_datasets:
  - path: winglian/latest-barley
    type: sharegpt
    conversation: mistral
    split: test
dataset_prepared_path: last_run_prepared
val_set_size: 0.0
output_dir: ./out

sequence_len: 4096
sample_packing: true
pad_to_sequence_len: true

wandb_project: relora-instruct-nous
wandb_entity: oaaic
wandb_watch:
wandb_name: fft
wandb_log_model:

gradient_accumulation_steps: 1
micro_batch_size: 4
num_epochs: 2
optimizer: adamw_bnb_8bit
adam_beta1: 0.95
adam_beta2: 0.9
adam_epsilon: 0.0001
max_grad_norm: 1.0
lr_scheduler: cosine
learning_rate: 0.000009
neftune_noise_alpha: 5

train_on_inputs: false
group_by_length: false
bf16: auto
fp16:
tf32: false

gradient_checkpointing: true
gradient_checkpointing_kwargs:
  use_reentrant: True
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true

warmup_steps: 20
evals_per_epoch: 4
eval_table_size:
saves_per_epoch: 2
debug:
deepspeed: deepspeed_configs/zero1.json # multi-gpu only
weight_decay: 0.1
fsdp:
fsdp_config:
special_tokens:

```

</details><br>

# titos

This model is a fine-tuned version of [tomaszki/nous-twelve](https://huggingface.co/tomaszki/nous-twelve) on the None 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: 9e-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.95,0.9) and epsilon=0.0001
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 20
- num_epochs: 2

### Training results



### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0