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---
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 |