---
base_model: mistralai/Mistral-7B-Instruct-v0.2
library_name: peft
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: finetune/outputs/medical
  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: `0.4.1`
```yaml
base_model: mistralai/Mistral-7B-Instruct-v0.2
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer

load_in_8bit: false
load_in_4bit: true
strict: false

chat_template: chatml
datasets:
  - path: Howard881010/medical
    type: alpaca
    train_on_split: train
dataset_prepared_path:
val_set_size: 0.05
output_dir: ./finetune/outputs/medical

adapter: qlora
lora_model_dir:

sequence_len: 1500
sample_packing: false
pad_to_sequence_len: true

lora_r: 32
lora_alpha: 16
lora_dropout: 0.05
lora_target_modules:
lora_target_linear: true
lora_fan_in_fan_out:

wandb_project: finetune
wandb_entity:
wandb_watch:
wandb_name: medical
wandb_log_model:

gradient_accumulation_steps: 2
micro_batch_size: 1
num_epochs: 10
optimizer: paged_adamw_32bit
lr_scheduler: cosine
learning_rate: 0.0002

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
eval_sample_packing: False

warmup_steps: 10
evals_per_epoch: 4
eval_table_size:
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
# For finetune
seed: 42

```

</details><br>

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://rosewandb.ucsd.edu/cht028/finetune/runs/b0fphoa0)
# finetune/outputs/medical

This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4607

## 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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- total_eval_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: 10

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 2.581         | 0.0005 | 1     | 2.3899          |
| 0.7439        | 0.2502 | 536   | 0.9957          |
| 0.6364        | 0.5004 | 1072  | 1.0250          |
| 0.4046        | 0.7505 | 1608  | 1.0972          |
| 0.2551        | 1.0007 | 2144  | 1.2306          |
| 0.1894        | 1.2509 | 2680  | 1.2541          |
| 0.1015        | 1.5011 | 3216  | 1.3733          |
| 0.1441        | 1.7512 | 3752  | 1.4618          |
| 0.0604        | 2.0014 | 4288  | 1.5229          |
| 0.058         | 2.2516 | 4824  | 1.5635          |
| 0.0669        | 2.5018 | 5360  | 1.6184          |
| 0.0604        | 2.7519 | 5896  | 1.6690          |
| 0.0352        | 3.0021 | 6432  | 1.6985          |
| 0.0296        | 3.2523 | 6968  | 1.7366          |
| 0.0262        | 3.5025 | 7504  | 1.7928          |
| 0.0214        | 3.7526 | 8040  | 1.8352          |
| 0.0134        | 4.0028 | 8576  | 1.9588          |
| 0.0108        | 4.2530 | 9112  | 1.9946          |
| 0.0112        | 4.5032 | 9648  | 1.9847          |
| 0.0107        | 4.7533 | 10184 | 1.9900          |
| 0.0052        | 5.0035 | 10720 | 2.0806          |
| 0.0067        | 5.2537 | 11256 | 2.1444          |
| 0.0053        | 5.5039 | 11792 | 2.2294          |
| 0.0055        | 5.7540 | 12328 | 2.3097          |
| 0.0067        | 6.0042 | 12864 | 2.3069          |
| 0.0004        | 6.2544 | 13400 | 2.3435          |
| 0.0005        | 6.5046 | 13936 | 2.2964          |
| 0.0004        | 6.7547 | 14472 | 2.3073          |
| 0.0002        | 7.0049 | 15008 | 2.3668          |
| 0.0002        | 7.2551 | 15544 | 2.3933          |
| 0.0001        | 7.5053 | 16080 | 2.4192          |
| 0.0002        | 7.7554 | 16616 | 2.4246          |
| 0.0001        | 8.0056 | 17152 | 2.4351          |
| 0.0001        | 8.2558 | 17688 | 2.4445          |
| 0.0002        | 8.5060 | 18224 | 2.4529          |
| 0.0002        | 8.7561 | 18760 | 2.4571          |
| 0.0001        | 9.0063 | 19296 | 2.4593          |
| 0.0001        | 9.2565 | 19832 | 2.4603          |
| 0.0001        | 9.5067 | 20368 | 2.4605          |
| 0.0013        | 9.7568 | 20904 | 2.4607          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.43.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1