---
library_name: transformers
license: apache-2.0
base_model: google-t5/t5-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: jackmedda/google-t5-t5-base_finetuned_augmented_augmented_phi4_14b
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# jackmedda/google-t5-t5-base_finetuned_augmented_augmented_phi4_14b

This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5423
- Accuracy: 0.7647
- F1: 0.8667
- Precision: 0.7647
- Recall: 1.0

## 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: 16
- eval_batch_size: 16
- 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: 50

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.5141        | 1.0   | 12   | 0.6293          | 0.7      | 0.8235 | 0.7       | 1.0    |
| 0.4405        | 2.0   | 24   | 0.7232          | 0.7      | 0.8235 | 0.7       | 1.0    |
| 0.3874        | 3.0   | 36   | 0.7399          | 0.7      | 0.8235 | 0.7       | 1.0    |
| 0.3841        | 4.0   | 48   | 0.7268          | 0.7      | 0.8235 | 0.7       | 1.0    |
| 0.4441        | 5.0   | 60   | 0.7062          | 0.7      | 0.8235 | 0.7       | 1.0    |
| 0.4177        | 6.0   | 72   | 0.6863          | 0.7      | 0.8235 | 0.7       | 1.0    |
| 0.3463        | 7.0   | 84   | 0.6922          | 0.7      | 0.8235 | 0.7       | 1.0    |
| 0.3713        | 8.0   | 96   | 0.7124          | 0.7      | 0.8235 | 0.7       | 1.0    |
| 0.3778        | 9.0   | 108  | 0.7128          | 0.7      | 0.8235 | 0.7       | 1.0    |


### Framework versions

- Transformers 4.48.2
- Pytorch 2.3.0+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0