README.md

---
license: apache-2.0
base_model: meta-math/MetaMath-Mistral-7B
tags:
- axolotl
- generated_from_trainer
model-index:
- name: EulerMath-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/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: meta-math/MetaMath-Mistral-7B
model_type: MistralForCausalLM
tokenizer_type: LlamaTokenizer
is_mistral_derived_model: true

load_in_8bit: false
load_in_4bit: false
strict: false

chat_template: alpaca
datasets:
  - path: microsoft/orca-math-word-problems-200k
    type: alpaca_chat.load_qa
    conversation: alpaca

  - path: TIGER-Lab/MathInstruct
    type: alpaca
    conversation: alpaca

dataset_prepared_path: last_run_prepared
val_set_size: 0.005
#val_set_size: 0.0

output_dir: ./EulerMath-Mistral-7B-model

sequence_len: 8192
sample_packing: true
pad_to_sequence_len: true
eval_sample_packing: false

wandb_project: Euler
wandb_entity:
wandb_watch:
wandb_name:
wandb_log_model:
hub_model_id: Weyaxi/EulerMath-Mistral-7B

save_safetensors: true

gradient_accumulation_steps: 4
micro_batch_size: 2 # changed
num_epochs: 2
optimizer: adamw_bnb_8bit
lr_scheduler: cosine
learning_rate: 0.000005

train_on_inputs: false
group_by_length: false
bf16: true
fp16: false
tf32: false

gradient_checkpointing: true
early_stopping_patience:
resume_from_checkpoint:
local_rank:
logging_steps: 1
xformers_attention:
flash_attention: true

warmup_steps: 10
evals_per_epoch: 4 # changed
eval_table_size:
eval_table_max_new_tokens: 128
saves_per_epoch: 1 # changed
debug:

deepspeed: zero3_bf16.json
weight_decay: 0.0
fsdp:
fsdp_config:
special_tokens:
  bos_token: "<s>"
  eos_token: "</s>"
  unk_token: "<unk>"

```

</details><br>

# EulerMath-Mistral-7B

This model is a fine-tuned version of [meta-math/MetaMath-Mistral-7B](https://huggingface.co/meta-math/MetaMath-Mistral-7B) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1956

## 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: 5e-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 9
- gradient_accumulation_steps: 4
- total_train_batch_size: 72
- total_eval_batch_size: 18
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.707         | 0.0   | 1    | 0.9061          |
| 0.3011        | 0.25  | 68   | 0.3263          |
| 0.2585        | 0.5   | 136  | 0.2836          |
| 0.2352        | 0.75  | 204  | 0.2544          |
| 0.2192        | 1.0   | 272  | 0.2268          |
| 0.1527        | 1.23  | 340  | 0.2144          |
| 0.1452        | 1.48  | 408  | 0.2032          |
| 0.144         | 1.73  | 476  | 0.1970          |
| 0.1441        | 1.98  | 544  | 0.1956          |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.2+cu118
- Datasets 2.18.0
- Tokenizers 0.15.0