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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: HuggingFaceTB/SmolLM2-135M-Instruct |
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tags: |
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- generated_from_trainer |
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- finance |
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model-index: |
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- name: check-amount-deverbalizer-smollm2 |
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results: [] |
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datasets: |
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- TrevorJS/check-amount-verbalizer-synthetic-data |
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language: |
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- en |
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pipeline_tag: text-generation |
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--- |
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# check-amount-deverbalizer-smollm2 |
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This model is a fine-tuned version of [HuggingFaceTB/SmolLM2-135M-Instruct](https://huggingface.co/HuggingFaceTB/SmolLM2-135M-Instruct) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1520 |
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- Json Parse Rate: 0.96 |
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- Dollar Accuracy: 0.96 |
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- Cents Accuracy: 0.96 |
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- Digit Count Accuracy: 0.96 |
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- Perfect Match: 0.96 |
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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: 5e-05 |
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- train_batch_size: 128 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- optimizer: Use OptimizerNames.ADAMW_TORCH 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: 100 |
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- num_epochs: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Json Parse Rate | Dollar Accuracy | Cents Accuracy | Digit Count Accuracy | Perfect Match | |
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|:-------------:|:------:|:----:|:---------------:|:---------------:|:---------------:|:--------------:|:--------------------:|:-------------:| |
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| 0.1588 | 0.2128 | 200 | 0.1580 | 0.9571 | 0.9271 | 0.9529 | 0.95 | 0.9186 | |
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| 0.1576 | 0.4255 | 400 | 0.1549 | 0.96 | 0.9557 | 0.96 | 0.96 | 0.9557 | |
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| 0.1546 | 0.6383 | 600 | 0.1539 | 0.96 | 0.9571 | 0.96 | 0.96 | 0.9571 | |
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| 0.154 | 0.8511 | 800 | 0.1541 | 0.9586 | 0.95 | 0.9586 | 0.9586 | 0.95 | |
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| 0.1539 | 1.0638 | 1000 | 0.1536 | 0.96 | 0.9557 | 0.96 | 0.96 | 0.9557 | |
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| 0.1544 | 1.2766 | 1200 | 0.1524 | 0.96 | 0.96 | 0.96 | 0.96 | 0.96 | |
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| 0.1535 | 1.4894 | 1400 | 0.1529 | 0.96 | 0.9571 | 0.96 | 0.96 | 0.9571 | |
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| 0.1537 | 1.7021 | 1600 | 0.1525 | 0.96 | 0.9586 | 0.96 | 0.96 | 0.9586 | |
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| 0.1548 | 1.9149 | 1800 | 0.1527 | 0.96 | 0.9586 | 0.96 | 0.96 | 0.9586 | |
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| 0.1545 | 2.1277 | 2000 | 0.1524 | 0.96 | 0.96 | 0.96 | 0.96 | 0.96 | |
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| 0.1534 | 2.3404 | 2200 | 0.1526 | 0.96 | 0.96 | 0.96 | 0.96 | 0.96 | |
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| 0.1533 | 2.5532 | 2400 | 0.1522 | 0.96 | 0.96 | 0.96 | 0.96 | 0.96 | |
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| 0.1524 | 2.7660 | 2600 | 0.1521 | 0.96 | 0.96 | 0.96 | 0.96 | 0.96 | |
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| 0.1527 | 2.9787 | 2800 | 0.1520 | 0.96 | 0.96 | 0.96 | 0.96 | 0.96 | |
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### Framework versions |
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- Transformers 4.48.2 |
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- Pytorch 2.5.1+cu124 |
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- Datasets 3.2.0 |
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- Tokenizers 0.21.0 |
