---
library_name: peft
license: apache-2.0
base_model: unsloth/mistral-7b
tags:
- axolotl
- generated_from_trainer
model-index:
- name: test-mistral-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/axolotl-ai-cloud/axolotl/main/image/axolotl-badge-web.png" alt="Built with Axolotl" width="200" height="32"/>](https://github.com/axolotl-ai-cloud/axolotl)
<details><summary>See axolotl config</summary>

axolotl version: `0.5.2`
```yaml
adapter: lora
base_model: unsloth/mistral-7b
bf16: auto
datasets:
- data_files:
  - 8219297a1f15c78f_train_data.json
  ds_type: json
  format: custom
  path: 8219297a1f15c78f_train_data.json
  preprocessing:
  - shuffle: true
  type:
    field: null
    field_input: null
    field_instruction: prompt
    field_output: response
    field_system: null
    format: null
    no_input_format: null
    system_format: '{system}'
    system_prompt: ''
debug: null
device_map: auto
early_stopping_patience: null
eval_max_new_tokens: 16
eval_table_max_new_tokens: 128
eval_table_size: null
evals_per_epoch: 8
flash_attention: true
fp16: null
fsdp: null
fsdp_config: null
gradient_accumulation_steps: 4
gradient_checkpointing: true
group_by_length: false
hub_model_id: taopanda/test-mistral-7b
is_mistral_derived_model: true
learning_rate: 0.0005
load_in_4bit: false
load_in_8bit: false
local_rank: null
logging_steps: 1
lora_alpha: 128
lora_dropout: 0.05
lora_r: 64
lora_target_modules:
- q_proj
- v_proj
lr_scheduler: cosine
max_grad_norm: 1.0
max_steps: 450
micro_batch_size: 4
model_type: MistralForCausalLM
num_epochs: 1
optimizer: adamw_torch
output_dir: ./out/taopanda_test-mistral-7b
pad_to_sequence_len: true
resume_from_checkpoint: null
save_steps: 0.15
save_total_limit: 1
seed: 42
sequence_len: 1024
special_tokens:
  bos_token: <s>
  eos_token: </s>
  unk_token: <unk>
strict: false
tf32: true
tokenizer_type: AutoTokenizer
train_on_inputs: false
trust_remote_code: true
use_flash_attn_2: true
val_set_size: 0.1
wandb_entity: fatcat87-taopanda
wandb_log_model: null
wandb_mode: online
wandb_name: taopanda_test-mistral-7b
wandb_project: subnet56-test
wandb_runid: taopanda_test-mistral-7b
wandb_watch: null
warmup_ratio: 0.06
weight_decay: 0.01
xformers_attention: null

```

</details><br>

# test-mistral-7b

This model is a fine-tuned version of [unsloth/mistral-7b](https://huggingface.co/unsloth/mistral-7b) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6985

## 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: 0.0005
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- total_eval_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 5
- training_steps: 87

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.0651        | 0.0116 | 1    | 1.0560          |
| 0.7617        | 0.1272 | 11   | 0.7764          |
| 0.7784        | 0.2543 | 22   | 0.7421          |
| 0.6848        | 0.3815 | 33   | 0.7290          |
| 0.7263        | 0.5087 | 44   | 0.7161          |
| 0.7062        | 0.6358 | 55   | 0.7074          |
| 0.7281        | 0.7630 | 66   | 0.7020          |
| 0.7402        | 0.8902 | 77   | 0.6985          |


### Framework versions

- PEFT 0.13.2
- Transformers 4.46.3
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3