widget:
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graph-regression
This model is a fine-tuned version of 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
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Model tree for PedroLancharesSanchez/graph-regression
Base model
clefourrier/graphormer-base-pcqm4mv2
Finetuned
this model