---
library_name: transformers
license: apache-2.0
base_model: T5-small
tags:
- generated_from_trainer
model-index:
- name: T5-OM
  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. -->

# T5-OM

This model is a fine-tuned version of [T5-small](https://huggingface.co/T5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0065
- Quadruple Accuracy: 0.3182

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Quadruple Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------------------:|
| 0.0528        | 1.0   | 468  | 0.0192          | 0.0138             |
| 0.0133        | 2.0   | 936  | 0.0091          | 0.2658             |
| 0.0169        | 3.0   | 1404 | 0.0077          | 0.2579             |
| 0.0115        | 4.0   | 1872 | 0.0072          | 0.2885             |
| 0.0104        | 5.0   | 2340 | 0.0069          | 0.3211             |
| 0.0078        | 6.0   | 2808 | 0.0067          | 0.3211             |
| 0.0094        | 7.0   | 3276 | 0.0066          | 0.3142             |
| 0.0072        | 8.0   | 3744 | 0.0065          | 0.3113             |
| 0.0084        | 9.0   | 4212 | 0.0065          | 0.3152             |
| 0.0064        | 10.0  | 4680 | 0.0065          | 0.3182             |


### Framework versions

- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0