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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_4_1
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_1
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: 0.0490
- 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 |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
| 0.6889 | 5.8501 | 50 | 0.6724 | 0.6073 | 0.5334 |
| 0.6445 | 11.7002 | 100 | 0.5323 | 0.8022 | 0.8091 |
| 0.3119 | 17.5503 | 150 | 0.1187 | 0.9649 | 0.9656 |
| 0.0967 | 23.4004 | 200 | 0.0648 | 0.9794 | 0.9800 |
| 0.0549 | 29.2505 | 250 | 0.0500 | 0.9858 | 0.9862 |
| 0.0359 | 35.1005 | 300 | 0.0465 | 0.9884 | 0.9888 |
| 0.0248 | 40.9506 | 350 | 0.0443 | 0.9887 | 0.9891 |
| 0.0183 | 46.8007 | 400 | 0.0404 | 0.9898 | 0.9902 |
| 0.0139 | 52.6508 | 450 | 0.0445 | 0.9890 | 0.9893 |
| 0.0111 | 58.5009 | 500 | 0.0559 | 0.9887 | 0.9890 |
| 0.0087 | 64.3510 | 550 | 0.0486 | 0.9893 | 0.9896 |
| 0.0081 | 70.2011 | 600 | 0.0440 | 0.9910 | 0.9913 |
| 0.0065 | 76.0512 | 650 | 0.0410 | 0.9919 | 0.9921 |
| 0.0045 | 81.9013 | 700 | 0.0596 | 0.9893 | 0.9896 |
| 0.0042 | 87.7514 | 750 | 0.0475 | 0.9898 | 0.9902 |
| 0.0036 | 93.6015 | 800 | 0.0490 | 0.9916 | 0.9919 |
### Framework versions
- Transformers 4.40.0
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1
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