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MetaMath-Qwen2.5-0.5b-PRM

Safetensors
qwen2
axolotl
Generated from Trainer
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MetaMath-Qwen2.5-0.5b-PRM
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---

license: apache-2.0
base_model: Qwen/Qwen2.5-0.5B
tags:
- axolotl
- generated_from_trainer
language:
- zho
- eng
- fra
- spa
- por
- deu
- ita
- rus
- jpn
- kor
- vie
- tha
- ara
model-index:
- name: MetaMath-Qwen2.5-0.5b-PRM
  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: `0.4.1`
```yaml

base_model: Qwen/Qwen2.5-0.5B

bf16: auto

dataset_prepared_path: /training/data/prepared

datasets:

- conversation: llama3

  path: RLHFlow/Mistral-PRM-Data

  split: train

  train_on_split: train

  type: sharegpt

flash_attention: true

fp16: false

gradient_accumulation_steps: 4

gradient_checkpointing: true

hub_model_id: rawsh/MetaMath-Qwen2.5-0.5b-PRM

hub_strategy: every_save

learning_rate: 2.0e-06

load_in_4bit: false

load_in_8bit: false

logging_steps: 2

lr_scheduler: cosine

max_grad_norm: 1.0

micro_batch_size: 1

model_type: AutoModelForCausalLM

num_epochs: 1

optimizer: paged_adamw_32bit

output_dir: /training/prm

pad_to_sequence_len: true

push_to_hub: true

sample_packing: true

save_safetensors: true

save_strategy: epoch

save_total_limit: 4

sequence_len: 8192

special_tokens:

  pad_token: <|endoftext|>

strict: false

tf32: true

tokenizer_type: AutoTokenizer

train_on_inputs: false

trust_remote_code: true

val_set_size: 0.0

wandb_name: qwen2.5-0.5b-bs32_lr2e-6_prm

wandb_project: preference-models

warmup_ratio: 0.05

weight_decay: 0.0



```

</details><br>

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/dankgpt/preference-models/runs/eqqhapl0)
# MetaMath-Qwen2.5-0.5b-PRM

This model is a fine-tuned version of [Qwen/Qwen2.5-0.5B](https://huggingface.co/Qwen/Qwen2.5-0.5B) on the None 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-06

- train_batch_size: 1

- eval_batch_size: 1

- seed: 42

- gradient_accumulation_steps: 4

- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 214

- num_epochs: 1

### Training results



### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1