---
license: apache-2.0
base_model: google-t5/t5-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: t5_es_farshad_half_2_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_2_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: 0.0404
- Accuracy: 0.9919
- F1: 0.9922

## 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     |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
| 0.7201        | 5.8501  | 50   | 0.6804          | 0.6244   | 0.6288 |
| 0.6469        | 11.7002 | 100  | 0.5235          | 0.8538   | 0.8578 |
| 0.3053        | 17.5503 | 150  | 0.1010          | 0.9690   | 0.9695 |
| 0.0887        | 23.4004 | 200  | 0.0576          | 0.9817   | 0.9823 |
| 0.051         | 29.2505 | 250  | 0.0453          | 0.9869   | 0.9873 |
| 0.0338        | 35.1005 | 300  | 0.0401          | 0.9898   | 0.9902 |
| 0.0232        | 40.9506 | 350  | 0.0416          | 0.9878   | 0.9882 |
| 0.0165        | 46.8007 | 400  | 0.0401          | 0.9904   | 0.9907 |
| 0.013         | 52.6508 | 450  | 0.0382          | 0.9913   | 0.9916 |
| 0.0108        | 58.5009 | 500  | 0.0433          | 0.9904   | 0.9907 |
| 0.0089        | 64.3510 | 550  | 0.0363          | 0.9933   | 0.9936 |
| 0.0074        | 70.2011 | 600  | 0.0421          | 0.9913   | 0.9916 |
| 0.0058        | 76.0512 | 650  | 0.0467          | 0.9913   | 0.9916 |
| 0.005         | 81.9013 | 700  | 0.0446          | 0.9916   | 0.9919 |
| 0.004         | 87.7514 | 750  | 0.0388          | 0.9925   | 0.9927 |
| 0.0033        | 93.6015 | 800  | 0.0404          | 0.9919   | 0.9922 |


### Framework versions

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