---
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