---
library_name: transformers
license: apache-2.0
base_model: mistralai/Mistral-7B-v0.1
tags:
- axolotl
- generated_from_trainer
datasets:
- custom
model-index:
- name: test
  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: `0.12.0.dev0`
```yaml
base_model: mistralai/Mistral-7B-v0.1
model_type: MistralForCausalLM
tokenizer_type: AutoTokenizer

datasets:
  - path: /workspace/axolotl/train_model/data/finetune_dataset.jsonl
    type:
      field_instruction: prompt
      field_output: response
      format: "[INST] {instruction} [/INST]"
      no_input_format: "[INST] {instruction} [/INST]"
      system_prompt: ""  # optionnel

val_set_size: 0.05
output_dir: /workspace/outputs-lovelace
hub_model_id: mikefol/test
sequence_len: 2048
sample_packing: true
eval_sample_packing: false

micro_batch_size: 4
gradient_accumulation_steps: 4
num_epochs: 3

optimizer: paged_adamw_32bit
lr_scheduler: cosine
learning_rate: 2e-5

gradient_checkpointing: true
use_wandb: false
push_to_hub: false
hub_private_repo: false
trust_remote_code: true

save_strategy: "no"
save_optimizer: false
save_safetensors: false

```

</details><br>

# test

This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the /workspace/axolotl/train_model/data/finetune_dataset.jsonl dataset.

## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use paged_adamw_32bit with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: cosine
- training_steps: 21

### Training results



### Framework versions

- Transformers 4.53.1
- Pytorch 2.7.1+cu126
- Datasets 3.6.0
- Tokenizers 0.21.2