---
base_model: eclec/patentClassificationLongFormer2
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: patentClassificationLongFormer3
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# patentClassificationLongFormer3

This model is a fine-tuned version of [eclec/patentClassificationLongFormer2](https://huggingface.co/eclec/patentClassificationLongFormer2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4056
- Accuracy: 0.8115
- F1: 0.5806

## 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: 1.3494108617032343e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 11
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.17770742346220472
- lr_scheduler_warmup_steps: 59
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.4232        | 1.0   | 1107 | 0.4202          | 0.8041   | 0.5957 |
| 0.3753        | 2.0   | 2215 | 0.4056          | 0.8115   | 0.5806 |
| 0.3157        | 3.0   | 3321 | 0.4318          | 0.8073   | 0.5949 |


### Framework versions

- Transformers 4.31.0
- Pytorch 2.0.0
- Datasets 2.14.4
- Tokenizers 0.13.3