---
library_name: transformers
license: bsd-3-clause
base_model: weathon/smiles_llava
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: smiles_llava_ft
  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. -->

# smiles_llava_ft

This model is a fine-tuned version of [weathon/smiles_llava](https://huggingface.co/weathon/smiles_llava) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0768
- Accuracy: 0.7191

## 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-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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: cosine
- lr_scheduler_warmup_ratio: 0.05
- num_epochs: 20
- mixed_precision_training: Native AMP
- label_smoothing_factor: 0.1

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 3.3041        | 0.9569  | 100  | 3.5557          | 0.0      |
| 2.3241        | 1.9091  | 200  | 2.5052          | 0.1835   |
| 2.029         | 2.8612  | 300  | 2.2936          | 0.5056   |
| 1.9409        | 3.8134  | 400  | 2.2173          | 0.5693   |
| 1.9861        | 4.7656  | 500  | 2.1782          | 0.6030   |
| 1.9564        | 5.7177  | 600  | 2.1461          | 0.6217   |
| 1.9314        | 6.6699  | 700  | 2.1301          | 0.6704   |
| 1.8838        | 7.6220  | 800  | 2.1084          | 0.6854   |
| 1.9538        | 8.5742  | 900  | 2.1052          | 0.7154   |
| 1.8382        | 9.5263  | 1000 | 2.0955          | 0.7191   |
| 1.9399        | 10.4785 | 1100 | 2.1008          | 0.6554   |
| 1.8231        | 11.4306 | 1200 | 2.0939          | 0.6891   |
| 1.8172        | 12.3828 | 1300 | 2.0899          | 0.6929   |
| 1.8708        | 13.3349 | 1400 | 2.0800          | 0.7491   |
| 1.915         | 14.2871 | 1500 | 2.0776          | 0.7116   |
| 1.8387        | 15.2392 | 1600 | 2.0819          | 0.7041   |
| 1.8646        | 16.1914 | 1700 | 2.0771          | 0.7228   |
| 1.7943        | 17.1435 | 1800 | 2.0770          | 0.7041   |
| 1.8878        | 18.0957 | 1900 | 2.0768          | 0.7154   |
| 1.841         | 19.0478 | 2000 | 2.0768          | 0.7191   |


### Framework versions

- Transformers 4.48.2
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0