---
base_model: mistralai/Mistral-7B-Instruct-v0.2
library_name: peft
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: finetune/outputs/climate
  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/climate
    type: alpaca
    train_on_split: train
dataset_prepared_path:
val_set_size: 0.05
output_dir: ./finetune/outputs/climate

adapter: qlora
lora_model_dir:

sequence_len: 2048
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: climate
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/xdu6khql)
# finetune/outputs/climate

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: 0.0009

## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 1.7472        | 0.0056 | 1    | 2.0532          |
| 1.1662        | 0.2542 | 45   | 1.2719          |
| 0.8512        | 0.5085 | 90   | 1.1146          |
| 1.141         | 0.7627 | 135  | 0.9757          |
| 0.5009        | 1.0169 | 180  | 0.7862          |
| 0.4804        | 1.2712 | 225  | 0.6073          |
| 0.3472        | 1.5254 | 270  | 0.4267          |
| 0.2733        | 1.7797 | 315  | 0.2808          |
| 0.1484        | 2.0339 | 360  | 0.1742          |
| 0.2064        | 2.2881 | 405  | 0.1261          |
| 0.1144        | 2.5424 | 450  | 0.0700          |
| 0.0787        | 2.7966 | 495  | 0.0390          |
| 0.0523        | 3.0508 | 540  | 0.0269          |
| 0.0606        | 3.3051 | 585  | 0.0193          |
| 0.0568        | 3.5593 | 630  | 0.0132          |
| 0.063         | 3.8136 | 675  | 0.0064          |
| 0.081         | 4.0678 | 720  | 0.0039          |
| 0.0748        | 4.3220 | 765  | 0.0022          |
| 0.0812        | 4.5763 | 810  | 0.0017          |
| 0.0313        | 4.8305 | 855  | 0.0015          |
| 0.0229        | 5.0847 | 900  | 0.0012          |
| 0.0518        | 5.3390 | 945  | 0.0011          |
| 0.019         | 5.5932 | 990  | 0.0011          |
| 0.09          | 5.8475 | 1035 | 0.0010          |
| 0.0907        | 6.1017 | 1080 | 0.0010          |
| 0.0876        | 6.3559 | 1125 | 0.0010          |
| 0.0716        | 6.6102 | 1170 | 0.0010          |
| 0.0728        | 6.8644 | 1215 | 0.0009          |
| 0.0338        | 7.1186 | 1260 | 0.0009          |
| 0.032         | 7.3729 | 1305 | 0.0009          |
| 0.0304        | 7.6271 | 1350 | 0.0009          |
| 0.0508        | 7.8814 | 1395 | 0.0009          |
| 0.0196        | 8.1356 | 1440 | 0.0009          |
| 0.0709        | 8.3898 | 1485 | 0.0009          |
| 0.0852        | 8.6441 | 1530 | 0.0009          |
| 0.0803        | 8.8983 | 1575 | 0.0009          |
| 0.1225        | 9.1525 | 1620 | 0.0009          |
| 0.0533        | 9.4068 | 1665 | 0.0009          |
| 0.0374        | 9.6610 | 1710 | 0.0009          |
| 0.0857        | 9.9153 | 1755 | 0.0009          |


### Framework versions

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