metadata
library_name: transformers
base_model: seyonec/PubChem10M_SMILES_BPE_450k
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: manotham-finetuneClassfication-AlzheimerDrug
results: []
manotham-finetuneClassfication-AlzheimerDrug
This model is a fine-tuned version of seyonec/PubChem10M_SMILES_BPE_450k on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2675
- Accuracy: 0.9383
- Precision: 0.9398
- Recall: 0.9383
- F1: 0.9382
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-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- 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 | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 75 | 0.2011 | 0.9408 | 0.9418 | 0.9408 | 0.9408 |
| No log | 2.0 | 150 | 0.2087 | 0.9475 | 0.9475 | 0.9475 | 0.9475 |
| No log | 3.0 | 225 | 0.2427 | 0.945 | 0.9457 | 0.945 | 0.9450 |
| No log | 4.0 | 300 | 0.2497 | 0.9417 | 0.9424 | 0.9417 | 0.9416 |
| No log | 5.0 | 375 | 0.2675 | 0.9383 | 0.9398 | 0.9383 | 0.9382 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1