|
|
--- |
|
|
base_model: alexyalunin/RuBioRoBERTa |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
metrics: |
|
|
- precision |
|
|
- recall |
|
|
- f1 |
|
|
- accuracy |
|
|
model-index: |
|
|
- name: nerel-bio-RuBioRoBERTa-base |
|
|
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. --> |
|
|
|
|
|
# nerel-bio-RuBioRoBERTa-base |
|
|
|
|
|
This model is a fine-tuned version of [alexyalunin/RuBioRoBERTa](https://huggingface.co/alexyalunin/RuBioRoBERTa) on an unknown dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.5262 |
|
|
- Precision: 0.8251 |
|
|
- Recall: 0.8335 |
|
|
- F1: 0.8293 |
|
|
- Accuracy: 0.8827 |
|
|
|
|
|
## 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: 5e-05 |
|
|
- train_batch_size: 6 |
|
|
- eval_batch_size: 6 |
|
|
- seed: 64 |
|
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
|
- lr_scheduler_type: cosine |
|
|
- lr_scheduler_warmup_ratio: 0.1 |
|
|
- num_epochs: 10 |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
|
|
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
|
|
| No log | 1.0 | 102 | 1.7932 | 0.4125 | 0.4094 | 0.4110 | 0.5484 | |
|
|
| No log | 2.0 | 204 | 0.5751 | 0.7711 | 0.7635 | 0.7673 | 0.8392 | |
|
|
| No log | 3.0 | 306 | 0.4426 | 0.8053 | 0.8163 | 0.8107 | 0.8727 | |
|
|
| No log | 4.0 | 408 | 0.4545 | 0.8070 | 0.8049 | 0.8060 | 0.8707 | |
|
|
| 0.8666 | 5.0 | 510 | 0.4854 | 0.8100 | 0.8024 | 0.8062 | 0.8693 | |
|
|
| 0.8666 | 6.0 | 612 | 0.4791 | 0.8194 | 0.8210 | 0.8202 | 0.8805 | |
|
|
| 0.8666 | 7.0 | 714 | 0.4975 | 0.8202 | 0.8306 | 0.8254 | 0.8816 | |
|
|
| 0.8666 | 8.0 | 816 | 0.4997 | 0.8217 | 0.8304 | 0.8260 | 0.8817 | |
|
|
| 0.8666 | 9.0 | 918 | 0.5237 | 0.8237 | 0.8318 | 0.8277 | 0.8821 | |
|
|
| 0.0548 | 10.0 | 1020 | 0.5262 | 0.8251 | 0.8335 | 0.8293 | 0.8827 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- Transformers 4.38.2 |
|
|
- Pytorch 2.2.1+cu121 |
|
|
- Datasets 2.19.0 |
|
|
- Tokenizers 0.15.2 |
|
|
|
