---
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: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# manotham-finetuneClassfication-AlzheimerDrug

This model is a fine-tuned version of [seyonec/PubChem10M_SMILES_BPE_450k](https://huggingface.co/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