---
library_name: transformers
license: mit
base_model: microsoft/git-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: 3d2smiles_pretrain
  results: []
---

<!-- 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. -->

# 3d2smiles_pretrain

This model is a fine-tuned version of [microsoft/git-base](https://huggingface.co/microsoft/git-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0178
- Accuracy: 0.9535

## 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: 1e-05
- train_batch_size: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 0.2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.0025        | 0.0448 | 100  | 0.0226          | 0.9244   |
| 0.0013        | 0.0896 | 200  | 0.0133          | 0.9244   |
| 0.0006        | 0.1343 | 300  | 0.0205          | 0.9419   |
| 0.0004        | 0.1791 | 400  | 0.0178          | 0.9535   |


### Framework versions

- Transformers 4.48.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0