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]] | |
<!-- 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. --> | |
# 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 | |