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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
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