---
license: apache-2.0
base_model: mistralai/Mistral-7B-v0.1
datasets:
- practical-dreamer/RPGPT_PublicDomain-alpaca
- shuyuej/metamath_gsm8k
- NeuralNovel/Neural-DPO
tags:
- generated_from_trainer
model-index:
- name: 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. -->

![image/jpeg](https://cdn-uploads.huggingface.co/production/uploads/645cfe4603fc86c46b3e46d1/FXt-g2q8JE-l77_gp23T3.jpeg)

# NeuralNovel/Senzu-7B-v0.1

Embracing a quiet *storm* ..


## Model Details

This model is a full parameter fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1)

Trained on the Neural-DPO, metamath_gsm8k and RPGPT_PublicDomain-alpaca dataset.

This model excels at character roleplay, also with the ability of responding accurately to a wide variety of complex questions.

```yaml
base_model: mistralai/Mistral-7B-v0.1
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer
is_mistral_derived_model: true

load_in_8bit: false
load_in_4bit: false
strict: false

datasets: 
  - path: practical-dreamer/RPGPT_PublicDomain-alpaca
    type: alpaca
    format: "[INST] {instruction} [/INST]"
    no_input_format: "[INST] {instruction} [/INST]"

datasets: 
  - path: shuyuej/metamath_gsm8k
    type: jeopardy
    format: "[INST] {instruction} [/INST]"
    no_input_format: "[INST] {instruction} [/INST]"

datasets:
  - path: NeuralNovel/Neural-DPO
    type:
      system_prompt: ""
      field_system: system
      field_instruction: chosen
      field_output: chosen
      format: "[INST] {instruction} [/INST]"
      no_input_format: "[INST] {instruction} [/INST]"
      
dataset_prepared_path:
val_set_size: 0.05
output_dir: ./out

sequence_len: 8192
sample_packing: false
pad_to_sequence_len: true
eval_sample_packing: false

wandb_project:
wandb_entity:
wandb_watch:
wandb_name: 
wandb_log_model:

gradient_accumulation_steps: 4
micro_batch_size: 2
num_epochs: 1
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.000005

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

gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true

warmup_steps: 10
evals_per_epoch: 4
eval_table_size:
eval_max_new_tokens: 128
saves_per_epoch: 0
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
  bos_token: "<s>"
  eos_token: "</s>"
  unk_token: "<unk>"

```

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 5e-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.2061        | 0.01  | 1    | 0.3139          |
| 0.0           | 0.25  | 32   | 0.0000          |
| 0.0           | 0.5   | 64   | 0.0010          |
| 0.0           | 0.76  | 96   | 0.0000          |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.2.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.0