---
library_name: peft
license: apache-2.0
base_model: mistralai/Mistral-Small-24B-Instruct-2501
tags:
- generated_from_trainer
datasets:
- data/data.jsonl
model-index:
- name: output
  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. -->

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<details><summary>See axolotl config</summary>

axolotl version: `0.8.1`
```yaml
base_model: mistralai/Mistral-Small-24B-Instruct-2501
model_type: AutoModelForCausalLM
tokenizer_type: AutoTokenizer

model_config:
  trust_remote_code: true
  tokenizer:
    pad_token: "</s>"
    padding_side: "right"
    add_bos_token: true
    add_eos_token: false

datasets:
  - path: data/data.jsonl
    type: chat_template
    chat_template_strategy: tokenizer
    field_messages: conversations
    message_property_mappings:
      role: role
      content: content
    roles:
      user: ["user"]
      assistant: ["assistant"]
      system: ["system"]

load_in_4bit: true
adapter: qlora
lora_r: 64
lora_alpha: 32
lora_dropout: 0.1
lora_target_modules:
  - q_proj
  - k_proj
  - v_proj
  - o_proj
  - gate_proj
  - up_proj
  - down_proj

bf16: true
flash_attention: true
gradient_checkpointing: true
deepspeed: deepspeed_configs/zero2.json

gradient_accumulation_steps: 4
micro_batch_size: 8
num_epochs: 3
optimizer: paged_adamw_8bit
lr_scheduler: cosine
learning_rate: 3e-6
warmup_ratio: 0.02

max_seq_length: 8192
pad_to_sequence_len: true
sample_packing: true
max_grad_norm: 1.0

output_dir: ./output
save_steps: 100
logging_steps: 10
save_safetensors: true

special_tokens:
  pad_token: "</s>"

```

</details><br>

# output

This model is a fine-tuned version of [mistralai/Mistral-Small-24B-Instruct-2501](https://huggingface.co/mistralai/Mistral-Small-24B-Instruct-2501) on the data/data.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: 3e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Use paged_adamw_8bit 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: 6
- num_epochs: 3.0

### Training results



### Framework versions

- PEFT 0.15.1
- Transformers 4.51.0
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1