---
license: apache-2.0
base_model: google-t5/t5-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: t5_es_farshad_half_4_2
  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_es_farshad_half_4_2

This model is a fine-tuned version of [google-t5/t5-base](https://huggingface.co/google-t5/t5-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0615
- Accuracy: 0.9896
- F1: 0.9899

## 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: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 64
- total_train_batch_size: 4096
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 100

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
| 0.6971        | 5.8501  | 50   | 0.6649          | 0.6589   | 0.6963 |
| 0.6328        | 11.7002 | 100  | 0.4862          | 0.8385   | 0.8422 |
| 0.2936        | 17.5503 | 150  | 0.1150          | 0.9626   | 0.9632 |
| 0.0908        | 23.4004 | 200  | 0.0712          | 0.9771   | 0.9776 |
| 0.0517        | 29.2505 | 250  | 0.0537          | 0.9846   | 0.9851 |
| 0.0342        | 35.1005 | 300  | 0.0500          | 0.9864   | 0.9867 |
| 0.0234        | 40.9506 | 350  | 0.0483          | 0.9884   | 0.9887 |
| 0.0166        | 46.8007 | 400  | 0.0522          | 0.9864   | 0.9867 |
| 0.0128        | 52.6508 | 450  | 0.0553          | 0.9869   | 0.9873 |
| 0.0099        | 58.5009 | 500  | 0.0559          | 0.9884   | 0.9887 |
| 0.0077        | 64.3510 | 550  | 0.0450          | 0.9901   | 0.9905 |
| 0.0061        | 70.2011 | 600  | 0.0477          | 0.9904   | 0.9907 |
| 0.0054        | 76.0512 | 650  | 0.0628          | 0.9867   | 0.9870 |
| 0.004         | 81.9013 | 700  | 0.0533          | 0.9896   | 0.9899 |
| 0.0039        | 87.7514 | 750  | 0.0445          | 0.9919   | 0.9921 |
| 0.0027        | 93.6015 | 800  | 0.0615          | 0.9896   | 0.9899 |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1