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---
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: t5_small_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_small_scotus
This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6132
- Accuracy: 0.515
- F1 Macro: 0.2879
- F1 Micro: 0.515
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 2.1902 | 0.32 | 50 | 2.1838 | 0.1686 | 0.0415 | 0.1686 |
| 1.7893 | 0.64 | 100 | 1.8675 | 0.4436 | 0.1774 | 0.4436 |
| 1.7871 | 0.96 | 150 | 1.7416 | 0.4529 | 0.2043 | 0.4529 |
| 1.5347 | 1.27 | 200 | 1.6757 | 0.485 | 0.2349 | 0.485 |
| 1.4821 | 1.59 | 250 | 1.6626 | 0.5079 | 0.2606 | 0.5079 |
| 1.3521 | 1.91 | 300 | 1.6865 | 0.5064 | 0.2680 | 0.5064 |
| 1.3616 | 2.23 | 350 | 1.6214 | 0.5093 | 0.2931 | 0.5093 |
| 1.2932 | 2.55 | 400 | 1.6142 | 0.5171 | 0.2861 | 0.5171 |
| 1.3028 | 2.87 | 450 | 1.6132 | 0.515 | 0.2879 | 0.515 |
### Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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