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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_4
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_4
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: 0.0456
- Accuracy: 0.9916
- F1: 0.9919
## 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 |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
| 0.8073 | 5.8501 | 50 | 0.7215 | 0.4858 | 0.0155 |
| 0.659 | 11.7002 | 100 | 0.5497 | 0.8353 | 0.8282 |
| 0.3485 | 17.5503 | 150 | 0.1162 | 0.9684 | 0.9692 |
| 0.0936 | 23.4004 | 200 | 0.0599 | 0.9814 | 0.9821 |
| 0.0492 | 29.2505 | 250 | 0.0447 | 0.9875 | 0.9880 |
| 0.0316 | 35.1005 | 300 | 0.0426 | 0.9898 | 0.9902 |
| 0.0215 | 40.9506 | 350 | 0.0411 | 0.9890 | 0.9894 |
| 0.0158 | 46.8007 | 400 | 0.0438 | 0.9907 | 0.9911 |
| 0.0131 | 52.6508 | 450 | 0.0389 | 0.9913 | 0.9916 |
| 0.0108 | 58.5009 | 500 | 0.0352 | 0.9927 | 0.9930 |
| 0.0092 | 64.3510 | 550 | 0.0376 | 0.9922 | 0.9924 |
| 0.0075 | 70.2011 | 600 | 0.0416 | 0.9916 | 0.9919 |
| 0.0063 | 76.0512 | 650 | 0.0403 | 0.9927 | 0.9930 |
| 0.0052 | 81.9013 | 700 | 0.0426 | 0.9925 | 0.9927 |
| 0.0045 | 87.7514 | 750 | 0.0443 | 0.9919 | 0.9922 |
| 0.0035 | 93.6015 | 800 | 0.0456 | 0.9916 | 0.9919 |
### Framework versions
- Transformers 4.40.0
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1
|