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license: apache-2.0
base_model: distilbert-base-uncased
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 is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6329
- Accuracy: 0.6441
- F1: 0.6528
- Precision: 0.6402
- Recall: 0.6658
## 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: 5.310370197342976e-05
- train_batch_size: 16
- eval_batch_size: 16
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
| 0.652 | 1.0 | 2221 | 0.6470 | 0.6087 | 0.5218 | 0.6759 | 0.4249 |
| 0.6283 | 2.0 | 4442 | 0.6329 | 0.6441 | 0.6528 | 0.6402 | 0.6658 |
| 0.5689 | 3.0 | 6663 | 0.6334 | 0.6371 | 0.6788 | 0.6112 | 0.7631 |
| 0.4785 | 4.0 | 8884 | 0.8592 | 0.6256 | 0.6131 | 0.6376 | 0.5905 |
| 0.3792 | 5.0 | 11105 | 0.9728 | 0.6207 | 0.6098 | 0.6310 | 0.5901 |
| 0.2839 | 6.0 | 13326 | 1.0226 | 0.6083 | 0.6212 | 0.6041 | 0.6394 |
| 0.2211 | 7.0 | 15547 | 1.6336 | 0.6145 | 0.6067 | 0.6223 | 0.5919 |
| 0.1756 | 8.0 | 17768 | 1.8340 | 0.6052 | 0.5951 | 0.6139 | 0.5773 |
| 0.1451 | 9.0 | 19989 | 2.0495 | 0.6078 | 0.5980 | 0.6165 | 0.5807 |
| 0.1147 | 10.0 | 22210 | 2.3889 | 0.6128 | 0.6128 | 0.6158 | 0.6098 |
| 0.0983 | 11.0 | 24431 | 2.4921 | 0.6119 | 0.6132 | 0.6141 | 0.6123 |
### Framework versions
- Transformers 4.31.0
- Pytorch 2.0.0
- Datasets 2.14.4
- Tokenizers 0.13.3
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