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---
library_name: transformers
license: apache-2.0
base_model: google/flan-t5-small
tags:
- generated_from_trainer
model-index:
- name: check-amount-deverbalizer-flan-t5-small
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. -->
# check-amount-deverbalizer-flan-t5-small
This model is a fine-tuned version of [google/flan-t5-small](https://huggingface.co/google/flan-t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0685
- Parse Rate: 1.0
- Dollar Accuracy: 0.9298
- Cents Accuracy: 0.9991
- Digit Count Accuracy: 1.0
- Perfect Match: 0.9296
## 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: 5e-05
- train_batch_size: 128
- eval_batch_size: 128
- 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 | Parse Rate | Dollar Accuracy | Cents Accuracy | Digit Count Accuracy | Perfect Match |
|:-------------:|:------:|:----:|:---------------:|:----------:|:---------------:|:--------------:|:--------------------:|:-------------:|
| 1.0914 | 0.2128 | 200 | 0.7008 | 0.9987 | 0.4598 | 0.8981 | 0.36 | 0.1972 |
| 0.6574 | 0.4255 | 400 | 0.3127 | 0.9999 | 0.6983 | 0.9889 | 0.8008 | 0.6573 |
| 0.4343 | 0.6383 | 600 | 0.1917 | 1.0 | 0.8006 | 0.9978 | 0.9763 | 0.7880 |
| 0.3524 | 0.8511 | 800 | 0.1484 | 1.0 | 0.8458 | 0.9979 | 0.9923 | 0.8407 |
| 0.2875 | 1.0638 | 1000 | 0.1249 | 1.0 | 0.8716 | 0.9982 | 0.9950 | 0.8682 |
| 0.2608 | 1.2766 | 1200 | 0.1089 | 1.0 | 0.8845 | 0.9985 | 0.9983 | 0.8827 |
| 0.2545 | 1.4894 | 1400 | 0.0974 | 1.0 | 0.8915 | 0.9981 | 0.9998 | 0.8909 |
| 0.2112 | 1.7021 | 1600 | 0.0895 | 1.0 | 0.8998 | 0.9988 | 1.0 | 0.8995 |
| 0.2074 | 1.9149 | 1800 | 0.0800 | 1.0 | 0.9128 | 0.9985 | 1.0 | 0.9124 |
| 0.1984 | 2.1277 | 2000 | 0.0766 | 1.0 | 0.9166 | 0.9987 | 1.0 | 0.9165 |
| 0.1837 | 2.3404 | 2200 | 0.0725 | 1.0 | 0.9246 | 0.9986 | 1.0 | 0.9245 |
| 0.1835 | 2.5532 | 2400 | 0.0705 | 1.0 | 0.9263 | 0.9991 | 1.0 | 0.9261 |
| 0.1743 | 2.7660 | 2600 | 0.0686 | 1.0 | 0.9313 | 0.9991 | 1.0 | 0.9311 |
| 0.1871 | 2.9787 | 2800 | 0.0685 | 1.0 | 0.9298 | 0.9991 | 1.0 | 0.9296 |
### Framework versions
- Transformers 4.48.2
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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