---
license: apache-2.0
library_name: peft
tags:
- axolotl
- generated_from_trainer
base_model: mistralai/Mistral-7B-v0.3
model-index:
- name: Mistral-7B-v0.3-deide-phi
  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-v0.3
model_type: MistralForCausalLM
tokenizer_type: LlamaTokenizer

load_in_8bit: true
load_in_4bit: false
strict: false

datasets:
  - path: thewimo/german-medical-identification-dataset-v0.1
    type: alpaca
dataset_prepared_path: last_run_prepared
val_set_size: 0.2
output_dir: ./outputs/lora-out
hub_model_id: thewimo/Mistral-7B-v0.3-deide-phi

adapter: lora
lora_model_dir:

sequence_len: 4096
sample_packing: false
pad_to_sequence_len: true

lora_r: 8
lora_alpha: 16
lora_dropout: 0.05
lora_target_linear: true
lora_fan_in_fan_out:
lora_target_modules:
  - gate_proj
  - down_proj
  - up_proj
  - q_proj
  - v_proj
  - k_proj
  - o_proj

wandb_project: axolotl-runs
wandb_entity: thewind-mom-finetuning 
wandb_watch:
wandb_name: Mistral-7B-v0.3-deide-phi
wandb_log_model:

gradient_accumulation_steps: 4
micro_batch_size: 4
num_epochs: 4
optimizer: paged_adamw_8bit
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

loss_watchdog_threshold: 5.0
loss_watchdog_patience: 3

warmup_steps: 10
evals_per_epoch: 4
eval_table_size:
eval_max_new_tokens: 128
saves_per_epoch: 1
debug:
deepspeed:
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:

```

</details><br>

# Mistral-7B-v0.3-deide-phi

This model is a fine-tuned version of [mistralai/Mistral-7B-v0.3](https://huggingface.co/mistralai/Mistral-7B-v0.3) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0364

## 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: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 3
- gradient_accumulation_steps: 4
- total_train_batch_size: 48
- total_eval_batch_size: 12
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 4

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.9682        | 0.0506 | 1    | 2.0579          |
| 1.2784        | 0.2532 | 5    | 0.8308          |
| 0.187         | 0.5063 | 10   | 0.1732          |
| 0.1094        | 0.7595 | 15   | 0.0819          |
| 0.0542        | 1.0127 | 20   | 0.0593          |
| 0.0354        | 1.2658 | 25   | 0.0521          |
| 0.0493        | 1.5190 | 30   | 0.0457          |
| 0.038         | 1.7722 | 35   | 0.0432          |
| 0.0143        | 2.0253 | 40   | 0.0425          |
| 0.0269        | 2.2785 | 45   | 0.0423          |
| 0.0273        | 2.5316 | 50   | 0.0415          |
| 0.0277        | 2.7848 | 55   | 0.0366          |
| 0.0288        | 3.0380 | 60   | 0.0356          |
| 0.0241        | 3.2911 | 65   | 0.0358          |
| 0.0125        | 3.5443 | 70   | 0.0362          |
| 0.0164        | 3.7975 | 75   | 0.0364          |


### Framework versions

- PEFT 0.10.0
- Transformers 4.40.2
- Pytorch 2.1.2+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1