---
library_name: transformers
license: mit
base_model: FacebookAI/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: a04f436e4d4e5de5b76ba7fd904c3c78
  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. -->

# a04f436e4d4e5de5b76ba7fd904c3c78

This model is a fine-tuned version of [FacebookAI/roberta-large](https://huggingface.co/FacebookAI/roberta-large) on the ccdv/patent-classification [abstract] dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3133
- Data Size: 1.0
- Epoch Runtime: 116.4855
- Accuracy: 0.6518
- F1 Macro: 0.5961

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Data Size | Epoch Runtime | Accuracy | F1 Macro |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:-------------:|:--------:|:--------:|
| No log        | 0     | 0     | 2.1164          | 0         | 7.2057        | 0.1510   | 0.0292   |
| No log        | 1     | 781   | 1.9938          | 0.0078    | 8.4663        | 0.2718   | 0.0863   |
| No log        | 2     | 1562  | 1.5860          | 0.0156    | 9.4765        | 0.3872   | 0.1908   |
| No log        | 3     | 2343  | 1.4555          | 0.0312    | 11.5807       | 0.4683   | 0.3026   |
| 0.0374        | 4     | 3124  | 1.3472          | 0.0625    | 15.1891       | 0.5483   | 0.4418   |
| 1.3362        | 5     | 3905  | 1.1729          | 0.125     | 21.9533       | 0.5645   | 0.5232   |
| 1.2058        | 6     | 4686  | 1.0861          | 0.25      | 36.7036       | 0.6178   | 0.5091   |
| 1.0744        | 7     | 5467  | 1.1440          | 0.5       | 63.8407       | 0.6174   | 0.5373   |
| 0.9986        | 8.0   | 6248  | 1.1125          | 1.0       | 121.1422      | 0.6314   | 0.5654   |
| 0.9276        | 9.0   | 7029  | 1.0343          | 1.0       | 123.2721      | 0.6502   | 0.5854   |
| 0.8526        | 10.0  | 7810  | 1.1100          | 1.0       | 119.2637      | 0.6482   | 0.5935   |
| 0.7286        | 11.0  | 8591  | 1.0734          | 1.0       | 118.6671      | 0.6601   | 0.6068   |
| 0.674         | 12.0  | 9372  | 1.2207          | 1.0       | 117.9967      | 0.6583   | 0.6129   |
| 0.558         | 13.0  | 10153 | 1.3133          | 1.0       | 116.4855      | 0.6518   | 0.5961   |


### Framework versions

- Transformers 4.57.0
- Pytorch 2.8.0+cu128
- Datasets 4.3.0
- Tokenizers 0.22.1