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