---
license: apache-2.0
library_name: peft
tags:
- axolotl
- generated_from_trainer
base_model: mistralai/Mistral-7B-v0.1
model-index:
- name: Mistral-of-Realms-7b
  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: mistralai/Mistral-7B-v0.1
base_model_config: mistralai/Mistral-7B-v0.1
model_type: MistralForCausalLM
tokenizer_type: LlamaTokenizer
is_mistral_derived_model: true
hub_model_id: Mistral-of-Realms-7b

load_in_8bit: false
load_in_4bit: true
strict: false

datasets:
  - path: Akila/ForgottenRealmsWikiDataset
    data_files:
      - specific_formats/FRW-J-axolotl-completion.jsonl
    type: completion
dataset_prepared_path: 
val_set_size: 0.02
output_dir: ./qlora-out

#using lora for lower cost
adapter: lora
lora_r: 8
lora_alpha: 16
lora_dropout: 0.05
lora_target_modules:
  - q_proj
  - v_proj

sequence_len: 512
sample_packing: false
pad_to_sequence_len: true

wandb_project:
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:

#only 2 epochs because of small dataset
gradient_accumulation_steps: 3
micro_batch_size: 2
num_epochs: 2
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.0002

train_on_inputs: false
group_by_length: false
bf16: true
fp16: false
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_table_max_new_tokens: 128
saves_per_epoch: 1
debug:
#default deepspeed, can use more aggresive if needed like zero2, zero3
deepspeed: 
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
  bos_token: "<s>"
  eos_token: "</s>"
  unk_token: "<unk>"
```

</details><br>

# Mistral-of-Realms-7b

This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the [Akila/ForgottenRealmsWikiDataset](https://huggingface.co/datasets/Akila/ForgottenRealmsWikiDataset) dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1762

## 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
- gradient_accumulation_steps: 3
- total_train_batch_size: 6
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| 2.4401        | 0.0   | 1     | 2.5991          |
| 2.3719        | 0.25  | 2224  | 2.2777          |
| 2.1262        | 0.5   | 4448  | 2.2483          |
| 2.3942        | 0.75  | 6672  | 2.2234          |
| 2.3839        | 1.0   | 8896  | 2.2065          |
| 2.5641        | 1.25  | 11120 | 2.1937          |
| 2.1295        | 1.5   | 13344 | 2.1821          |
| 1.7813        | 1.75  | 15568 | 2.1773          |
| 1.9467        | 2.0   | 17792 | 2.1762          |


### Framework versions

- PEFT 0.7.2.dev0
- Transformers 4.37.0
- Pytorch 2.1.2+cu118
- Datasets 2.16.1
- Tokenizers 0.15.0