---
library_name: peft
license: gemma
base_model: google/t5gemma-s-s-ul2-it
tags:
- base_model:adapter:google/t5gemma-s-s-ul2-it
- lora
- transformers
model-index:
- name: t5gemma-math-corrector
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# t5gemma-math-corrector

This model is a fine-tuned version of [google/t5gemma-s-s-ul2-it](https://huggingface.co/google/t5gemma-s-s-ul2-it) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 7.1757

## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.0108        | 0.6774 | 200  | 4.4378          |
| 0.0034        | 1.3522 | 400  | 7.0770          |
| 0.002         | 2.0271 | 600  | 7.6245          |
| 0.0011        | 2.7045 | 800  | 7.1757          |


### Framework versions

- PEFT 0.17.1
- Transformers 4.55.2
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.21.4