---
license: apache-2.0
base_model: distilbert/distilroberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilroberta_base_patent
  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_patent

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: 1.0022
- Accuracy: 0.6596
- F1 Macro: 0.5725
- F1 Micro: 0.6596

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 1.5474        | 0.13  | 50   | 1.4682          | 0.4644   | 0.3007   | 0.4644   |
| 1.2975        | 0.26  | 100  | 1.2702          | 0.5514   | 0.3857   | 0.5514   |
| 1.277         | 0.38  | 150  | 1.1989          | 0.588    | 0.4213   | 0.588    |
| 1.1483        | 0.51  | 200  | 1.1509          | 0.6018   | 0.4433   | 0.6018   |
| 1.1909        | 0.64  | 250  | 1.1209          | 0.618    | 0.4785   | 0.618    |
| 1.1243        | 0.77  | 300  | 1.1128          | 0.622    | 0.4930   | 0.622    |
| 1.1353        | 0.9   | 350  | 1.1134          | 0.609    | 0.4930   | 0.609    |
| 1.0636        | 1.02  | 400  | 1.0676          | 0.64     | 0.5189   | 0.64     |
| 0.9667        | 1.15  | 450  | 1.0703          | 0.6404   | 0.5193   | 0.6404   |
| 1.0063        | 1.28  | 500  | 1.0495          | 0.6386   | 0.5128   | 0.6386   |
| 0.9521        | 1.41  | 550  | 1.0469          | 0.6432   | 0.5185   | 0.6432   |
| 0.998         | 1.53  | 600  | 1.0359          | 0.6486   | 0.5357   | 0.6486   |
| 1.0188        | 1.66  | 650  | 1.0530          | 0.6418   | 0.5395   | 0.6418   |
| 0.9617        | 1.79  | 700  | 1.0214          | 0.6526   | 0.5307   | 0.6526   |
| 1.0234        | 1.92  | 750  | 1.0148          | 0.6514   | 0.5495   | 0.6514   |
| 0.8914        | 2.05  | 800  | 1.0132          | 0.6544   | 0.5603   | 0.6544   |
| 0.9269        | 2.17  | 850  | 1.0110          | 0.6562   | 0.5647   | 0.6562   |
| 1.0351        | 2.3   | 900  | 1.0124          | 0.6528   | 0.5717   | 0.6528   |
| 0.9582        | 2.43  | 950  | 1.0150          | 0.6524   | 0.5552   | 0.6524   |
| 0.8959        | 2.56  | 1000 | 1.0069          | 0.659    | 0.5741   | 0.659    |
| 0.8342        | 2.69  | 1050 | 1.0031          | 0.6596   | 0.5794   | 0.6596   |
| 0.883         | 2.81  | 1100 | 1.0042          | 0.6594   | 0.5767   | 0.6594   |
| 0.9377        | 2.94  | 1150 | 1.0022          | 0.6596   | 0.5725   | 0.6596   |


### Framework versions

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