---
library_name: peft
license: apache-2.0
base_model: HuggingFaceTB/SmolVLM-Base
tags:
- base_model:adapter:HuggingFaceTB/SmolVLM-Base
- lora
- transformers
metrics:
- wer
model-index:
- name: SmolVLM-Base-ocr-isl
  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. -->

# SmolVLM-Base-ocr-isl

This model is a fine-tuned version of [HuggingFaceTB/SmolVLM-Base](https://huggingface.co/HuggingFaceTB/SmolVLM-Base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0420
- Wer: 0.4108
- Cer: 0.4556
- Exact Match: 0.0
- Special Char Acc: 0.0084
- Seq Acc 5: 0.0
- Seq Acc 10: 0.0

## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    | Cer    | Exact Match | Special Char Acc | Seq Acc 5 | Seq Acc 10 |
|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:-----------:|:----------------:|:---------:|:----------:|
| 0.1564        | 0.1245 | 500  | 0.1101          | 0.4213 | 0.5448 | 0.0         | 0.0140           | 0.0       | 0.0        |
| 0.0866        | 0.2490 | 1000 | 0.0791          | 0.3409 | 0.4947 | 0.0         | 0.0112           | 0.0       | 0.0        |
| 0.1093        | 0.3735 | 1500 | 0.0646          | 0.4073 | 0.4989 | 0.0         | 0.0140           | 0.0       | 0.0        |
| 0.1016        | 0.4979 | 2000 | 0.0570          | 0.3951 | 0.4507 | 0.0         | 0.0056           | 0.0       | 0.0        |
| 0.1           | 0.6224 | 2500 | 0.0504          | 0.4318 | 0.5059 | 0.0         | 0.0169           | 0.0       | 0.0        |
| 0.0777        | 0.7469 | 3000 | 0.0415          | 0.4248 | 0.4692 | 0.0         | 0.0140           | 0.0       | 0.0        |
| 0.107         | 0.8714 | 3500 | 0.0427          | 0.4021 | 0.4732 | 0.0         | 0.0140           | 0.0       | 0.0        |
| 0.1286        | 0.9959 | 4000 | 0.0420          | 0.4108 | 0.4556 | 0.0         | 0.0084           | 0.0       | 0.0        |


### Framework versions

- PEFT 0.17.1
- Transformers 4.56.2
- Pytorch 2.8.0+cu128
- Datasets 4.1.0
- Tokenizers 0.22.1