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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_weight_2_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_weight_2_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: 0.0241
- Accuracy: 0.997
- F1: 0.9972
## 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 |
|:-------------:|:-------:|:----:|:---------------:|:--------:|:------:|
| 0.7035 | 6.8817 | 50 | 0.6738 | 0.7045 | 0.7288 |
| 0.6463 | 13.7634 | 100 | 0.5114 | 0.8975 | 0.9015 |
| 0.2909 | 20.6452 | 150 | 0.0785 | 0.977 | 0.9783 |
| 0.0595 | 27.5269 | 200 | 0.0455 | 0.987 | 0.9878 |
| 0.0286 | 34.4086 | 250 | 0.0283 | 0.992 | 0.9925 |
| 0.0158 | 41.2903 | 300 | 0.0219 | 0.9945 | 0.9948 |
| 0.0086 | 48.1720 | 350 | 0.0180 | 0.996 | 0.9962 |
| 0.0048 | 55.0538 | 400 | 0.0172 | 0.9955 | 0.9958 |
| 0.0031 | 61.9355 | 450 | 0.0223 | 0.9955 | 0.9958 |
| 0.002 | 68.8172 | 500 | 0.0199 | 0.9955 | 0.9958 |
| 0.0012 | 75.6989 | 550 | 0.0201 | 0.9965 | 0.9967 |
| 0.0008 | 82.5806 | 600 | 0.0190 | 0.997 | 0.9972 |
| 0.0008 | 89.4624 | 650 | 0.0205 | 0.997 | 0.9972 |
| 0.0007 | 96.3441 | 700 | 0.0241 | 0.997 | 0.9972 |
### Framework versions
- Transformers 4.40.0
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1
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