---
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