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---
license: apache-2.0
base_model: google-t5/t5-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: t5_base_scotus
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_base_scotus
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: 1.5028
- Accuracy: 0.5657
- F1 Macro: 0.4059
- F1 Micro: 0.5657
## 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: 0.0005
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Micro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 2.0135 | 0.32 | 50 | 1.9644 | 0.3357 | 0.0896 | 0.3357 |
| 1.6667 | 0.64 | 100 | 1.7576 | 0.455 | 0.2229 | 0.455 |
| 1.6764 | 0.96 | 150 | 1.6189 | 0.4914 | 0.2459 | 0.4914 |
| 1.3803 | 1.27 | 200 | 1.6398 | 0.4814 | 0.2690 | 0.4814 |
| 1.315 | 1.59 | 250 | 1.5466 | 0.5471 | 0.3480 | 0.5471 |
| 1.229 | 1.91 | 300 | 1.5177 | 0.5543 | 0.3855 | 0.5543 |
| 1.0902 | 2.23 | 350 | 1.5300 | 0.5586 | 0.3977 | 0.5586 |
| 1.0522 | 2.55 | 400 | 1.5028 | 0.5657 | 0.4059 | 0.5657 |
| 0.9946 | 2.87 | 450 | 1.5198 | 0.5629 | 0.4060 | 0.5629 |
### Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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