---
license: mit
base_model: clefourrier/pcqm4mv2_graphormer_base
tags:
- generated_from_trainer
model-index:
- name: graph-regression
  results: []
---

widget:
- structured_data:
  node_feat:
    -[[0],[0],[0],[0],[0],[0],[0],[0],[1],[0],[0],[0],[0],[1],[2],[0],[0],[0],[0],[0],[0],[3],[0],[0]],
  edge_index:
    -[[0, 1, 1, 1, 1, 2, 3, 4, 4, 4, 5, 5, 6, 6, 7, 7, 7, 8, 8, 9, 9, 10, 10, 10, 11, 11, 12, 12, 12, 13, 14, 14, 15, 15, 15, 16, 16, 17, 17, 18, 18, 19, 19, 20, 20, 20, 21, 22, 22, 22, 23, 23],[1, 0, 2, 3, 4, 1, 1, 1, 5, 23, 4, 6, 5, 7, 6, 8, 22, 7, 9, 8, 10, 9, 11, 22, 10, 12, 11, 13, 14, 12, 12, 15, 14, 16, 20, 15, 17, 16, 18, 17, 19, 18, 20, 15, 19, 21, 20, 7, 10, 23, 4, 22]]
  

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# graph-regression

This model is a fine-tuned version of [clefourrier/pcqm4mv2_graphormer_base](https://huggingface.co/clefourrier/pcqm4mv2_graphormer_base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 7.6257

## 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-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 10
- total_train_batch_size: 640
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 18.2131       | 0.8861 | 7    | 10.2140         |
| 6.1806        | 1.8987 | 15   | 9.1356          |
| 5.1328        | 2.9114 | 23   | 8.2925          |
| 4.392         | 3.9241 | 31   | 7.6640          |
| 3.4272        | 4.4304 | 35   | 7.6257          |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1