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

# distilbert_base_uncased_patent

This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9811
- Accuracy: 0.6632
- F1 Macro: 0.5701
- F1 Micro: 0.6632

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 1.5572        | 0.13  | 50   | 1.4884          | 0.504    | 0.3171   | 0.504    |
| 1.2925        | 0.26  | 100  | 1.2877          | 0.5634   | 0.3803   | 0.5634   |
| 1.253         | 0.38  | 150  | 1.2014          | 0.5974   | 0.4162   | 0.5974   |
| 1.1591        | 0.51  | 200  | 1.1558          | 0.6102   | 0.4468   | 0.6102   |
| 1.1756        | 0.64  | 250  | 1.1151          | 0.6244   | 0.4725   | 0.6244   |
| 1.1078        | 0.77  | 300  | 1.1123          | 0.6268   | 0.4912   | 0.6268   |
| 1.1463        | 0.9   | 350  | 1.0832          | 0.627    | 0.5030   | 0.627    |
| 1.0328        | 1.02  | 400  | 1.0610          | 0.6432   | 0.5068   | 0.6432   |
| 0.9224        | 1.15  | 450  | 1.0462          | 0.6476   | 0.5153   | 0.6476   |
| 0.9902        | 1.28  | 500  | 1.0401          | 0.6448   | 0.5168   | 0.6448   |
| 0.9681        | 1.41  | 550  | 1.0253          | 0.6546   | 0.5216   | 0.6546   |
| 0.9657        | 1.53  | 600  | 1.0123          | 0.6564   | 0.5248   | 0.6564   |
| 0.9742        | 1.66  | 650  | 1.0186          | 0.656    | 0.5263   | 0.656    |
| 0.9443        | 1.79  | 700  | 1.0028          | 0.66     | 0.5279   | 0.66     |
| 0.9944        | 1.92  | 750  | 1.0000          | 0.6544   | 0.5324   | 0.6544   |
| 0.849         | 2.05  | 800  | 0.9939          | 0.6588   | 0.5571   | 0.6588   |
| 0.8801        | 2.17  | 850  | 0.9916          | 0.6608   | 0.5618   | 0.6608   |
| 0.9913        | 2.3   | 900  | 0.9912          | 0.6634   | 0.5686   | 0.6634   |
| 0.923         | 2.43  | 950  | 0.9879          | 0.666    | 0.5739   | 0.666    |
| 0.8935        | 2.56  | 1000 | 0.9828          | 0.6642   | 0.5695   | 0.6642   |
| 0.8062        | 2.69  | 1050 | 0.9877          | 0.6598   | 0.5691   | 0.6598   |
| 0.853         | 2.81  | 1100 | 0.9811          | 0.6632   | 0.5701   | 0.6632   |
| 0.8978        | 2.94  | 1150 | 0.9811          | 0.6638   | 0.5709   | 0.6638   |


### Framework versions

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