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---
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: patentClassfication2
  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. -->

# patentClassfication2

This model was trained from scratch on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6212
- Accuracy: 0.6754
- F1: 0.7015
- Precision: 0.6475
- Recall: 0.7653

## 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: 1.939963e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 40
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 11

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1     | Precision | Recall |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.6217        | 1.0   | 4438  | 0.6251          | 0.6405   | 0.5425 | 0.7414    | 0.4278 |
| 0.5918        | 2.0   | 8876  | 0.6212          | 0.6754   | 0.7015 | 0.6475    | 0.7653 |
| 0.5097        | 3.0   | 13314 | 0.8241          | 0.6748   | 0.6827 | 0.6645    | 0.7020 |
| 0.4099        | 4.0   | 17752 | 1.0772          | 0.6685   | 0.6810 | 0.6542    | 0.7102 |
| 0.3342        | 5.0   | 22190 | 1.7059          | 0.6550   | 0.6645 | 0.6446    | 0.6857 |
| 0.216         | 6.0   | 26628 | 2.1970          | 0.6503   | 0.6529 | 0.6459    | 0.6600 |
| 0.1214        | 7.0   | 31066 | 2.7215          | 0.6498   | 0.6642 | 0.6360    | 0.6950 |
| 0.0548        | 8.0   | 35504 | 2.9805          | 0.6515   | 0.6557 | 0.6458    | 0.6658 |
| 0.0356        | 9.0   | 39942 | 3.2608          | 0.6541   | 0.6560 | 0.6503    | 0.6618 |
| 0.0284        | 10.0  | 44380 | 3.3810          | 0.6513   | 0.6548 | 0.6461    | 0.6638 |
| 0.0186        | 11.0  | 48818 | 3.3967          | 0.6514   | 0.6576 | 0.6440    | 0.6717 |


### Framework versions

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