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---
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
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