---
license: apache-2.0
base_model: distilbert/distilroberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilroberta_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. -->

# distilroberta_base_scotus

This model is a fine-tuned version of [distilbert/distilroberta-base](https://huggingface.co/distilbert/distilroberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6983
- Accuracy: 0.4914
- F1 Macro: 0.1888
- F1 Micro: 0.4914

## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 64
- total_eval_batch_size: 64
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 2.0217        | 0.63  | 50   | 2.0067          | 0.3879   | 0.0997   | 0.3879   |
| 1.6626        | 1.27  | 100  | 1.8174          | 0.4421   | 0.1288   | 0.4421   |
| 1.7473        | 1.9   | 150  | 1.7735          | 0.4486   | 0.1535   | 0.4486   |
| 1.5993        | 2.53  | 200  | 1.6983          | 0.4914   | 0.1888   | 0.4914   |


### Framework versions

- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2