---
library_name: transformers
license: llama3.1
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: prm_version3_full_hf
  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. -->

# prm_version3_full_hf

This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B-Instruct) on the prm_conversations_prm_version3_math+webinstructsub-mcq+webinstructsub-oe+apps+gsm_mix_ref_hf dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1166

## 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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step  | Validation Loss |
|:-------------:|:------:|:-----:|:---------------:|
| 0.1961        | 0.0461 | 500   | 0.2069          |
| 0.192         | 0.0921 | 1000  | 0.1930          |
| 0.1963        | 0.1382 | 1500  | 0.1833          |
| 0.1701        | 0.1843 | 2000  | 0.1748          |
| 0.1647        | 0.2303 | 2500  | 0.1687          |
| 0.1507        | 0.2764 | 3000  | 0.1630          |
| 0.1421        | 0.3225 | 3500  | 0.1579          |
| 0.1403        | 0.3685 | 4000  | 0.1528          |
| 0.1557        | 0.4146 | 4500  | 0.1485          |
| 0.1536        | 0.4607 | 5000  | 0.1441          |
| 0.1344        | 0.5067 | 5500  | 0.1399          |
| 0.1195        | 0.5528 | 6000  | 0.1355          |
| 0.1209        | 0.5989 | 6500  | 0.1316          |
| 0.137         | 0.6450 | 7000  | 0.1284          |
| 0.117         | 0.6910 | 7500  | 0.1253          |
| 0.116         | 0.7371 | 8000  | 0.1228          |
| 0.1259        | 0.7832 | 8500  | 0.1206          |
| 0.1147        | 0.8292 | 9000  | 0.1187          |
| 0.1175        | 0.8753 | 9500  | 0.1175          |
| 0.1117        | 0.9214 | 10000 | 0.1168          |
| 0.1133        | 0.9674 | 10500 | 0.1166          |


### Framework versions

- Transformers 4.45.0
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3