---
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_trainer
datasets:
- patent-classification
metrics:
- accuracy
model-index:
- name: roberta_base_patent
  results:
  - task:
      name: Text Classification
      type: text-classification
    dataset:
      name: patent-classification
      type: patent-classification
      config: abstract
      split: validation
      args: abstract
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.679
---

<!-- 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. -->

# roberta_base_patent

This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on the patent-classification dataset.
It achieves the following results on the evaluation set:
- Loss: 0.9374
- Accuracy: 0.679
- F1 Macro: 0.6098
- F1 Micro: 0.679

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 1.5014        | 0.13  | 50   | 1.4249          | 0.5094   | 0.3519   | 0.5094   |
| 1.2516        | 0.26  | 100  | 1.2353          | 0.5716   | 0.4110   | 0.5716   |
| 1.2231        | 0.38  | 150  | 1.1279          | 0.6184   | 0.4706   | 0.6184   |
| 1.1169        | 0.51  | 200  | 1.0773          | 0.6346   | 0.5016   | 0.6346   |
| 1.1195        | 0.64  | 250  | 1.0686          | 0.6398   | 0.5182   | 0.6398   |
| 1.0737        | 0.77  | 300  | 1.0548          | 0.6426   | 0.5232   | 0.6426   |
| 1.0981        | 0.9   | 350  | 1.0438          | 0.6376   | 0.5605   | 0.6376   |
| 1.0147        | 1.02  | 400  | 0.9970          | 0.6606   | 0.5852   | 0.6606   |
| 0.9049        | 1.15  | 450  | 1.0098          | 0.6572   | 0.5804   | 0.6572   |
| 0.945         | 1.28  | 500  | 0.9907          | 0.662    | 0.5873   | 0.662    |
| 0.9206        | 1.41  | 550  | 0.9865          | 0.6636   | 0.5777   | 0.6636   |
| 0.9263        | 1.53  | 600  | 0.9686          | 0.6664   | 0.5968   | 0.6664   |
| 0.9629        | 1.66  | 650  | 0.9791          | 0.666    | 0.5941   | 0.666    |
| 0.8913        | 1.79  | 700  | 0.9579          | 0.6746   | 0.6002   | 0.6746   |
| 0.96          | 1.92  | 750  | 0.9524          | 0.6696   | 0.6025   | 0.6696   |
| 0.8284        | 2.05  | 800  | 0.9540          | 0.6738   | 0.6073   | 0.6738   |
| 0.8558        | 2.17  | 850  | 0.9496          | 0.6742   | 0.5949   | 0.6742   |
| 0.9643        | 2.3   | 900  | 0.9520          | 0.6748   | 0.6074   | 0.6748   |
| 0.873         | 2.43  | 950  | 0.9521          | 0.6732   | 0.5963   | 0.6732   |
| 0.8271        | 2.56  | 1000 | 0.9399          | 0.6782   | 0.6123   | 0.6782   |
| 0.7572        | 2.69  | 1050 | 0.9400          | 0.6788   | 0.6076   | 0.6788   |
| 0.7949        | 2.81  | 1100 | 0.9386          | 0.6808   | 0.6099   | 0.6808   |
| 0.8183        | 2.94  | 1150 | 0.9374          | 0.679    | 0.6098   | 0.679    |


### Framework versions

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