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--- |
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library_name: peft |
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license: apache-2.0 |
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base_model: HuggingFaceTB/SmolVLM-Base |
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tags: |
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- base_model:adapter:HuggingFaceTB/SmolVLM-Base |
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- lora |
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- transformers |
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metrics: |
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- wer |
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model-index: |
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- name: SmolVLM-Base-ocr-isl |
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results: [] |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# SmolVLM-Base-ocr-isl |
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This model is a fine-tuned version of [HuggingFaceTB/SmolVLM-Base](https://huggingface.co/HuggingFaceTB/SmolVLM-Base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0420 |
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- Wer: 0.4108 |
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- Cer: 0.4556 |
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- Exact Match: 0.0 |
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- Special Char Acc: 0.0084 |
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- Seq Acc 5: 0.0 |
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- Seq Acc 10: 0.0 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0001 |
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- train_batch_size: 4 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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- optimizer: Use OptimizerNames.PAGED_ADAMW_8BIT with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 50 |
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- num_epochs: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | Exact Match | Special Char Acc | Seq Acc 5 | Seq Acc 10 | |
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|:-------------:|:------:|:----:|:---------------:|:------:|:------:|:-----------:|:----------------:|:---------:|:----------:| |
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| 0.1564 | 0.1245 | 500 | 0.1101 | 0.4213 | 0.5448 | 0.0 | 0.0140 | 0.0 | 0.0 | |
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| 0.0866 | 0.2490 | 1000 | 0.0791 | 0.3409 | 0.4947 | 0.0 | 0.0112 | 0.0 | 0.0 | |
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| 0.1093 | 0.3735 | 1500 | 0.0646 | 0.4073 | 0.4989 | 0.0 | 0.0140 | 0.0 | 0.0 | |
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| 0.1016 | 0.4979 | 2000 | 0.0570 | 0.3951 | 0.4507 | 0.0 | 0.0056 | 0.0 | 0.0 | |
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| 0.1 | 0.6224 | 2500 | 0.0504 | 0.4318 | 0.5059 | 0.0 | 0.0169 | 0.0 | 0.0 | |
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| 0.0777 | 0.7469 | 3000 | 0.0415 | 0.4248 | 0.4692 | 0.0 | 0.0140 | 0.0 | 0.0 | |
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| 0.107 | 0.8714 | 3500 | 0.0427 | 0.4021 | 0.4732 | 0.0 | 0.0140 | 0.0 | 0.0 | |
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| 0.1286 | 0.9959 | 4000 | 0.0420 | 0.4108 | 0.4556 | 0.0 | 0.0084 | 0.0 | 0.0 | |
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### Framework versions |
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- PEFT 0.17.1 |
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- Transformers 4.56.2 |
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- Pytorch 2.8.0+cu128 |
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- Datasets 4.1.0 |
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- Tokenizers 0.22.1 |
