|
|
--- |
|
|
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 |
|
|
|
