---
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