|
--- |
|
library_name: transformers |
|
base_model: allenai/biomed_roberta_base |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- precision |
|
- recall |
|
- f1 |
|
- accuracy |
|
model-index: |
|
- name: BioMedRoBERTa-finetuned-valid-testing-0.0001-16 |
|
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. --> |
|
|
|
# BioMedRoBERTa-finetuned-valid-testing-0.0001-16 |
|
|
|
This model is a fine-tuned version of [allenai/biomed_roberta_base](https://huggingface.co/allenai/biomed_roberta_base) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.0924 |
|
- Precision: 0.8156 |
|
- Recall: 0.8242 |
|
- F1: 0.8199 |
|
- Accuracy: 0.9768 |
|
|
|
## 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: 0.0001 |
|
- train_batch_size: 16 |
|
- eval_batch_size: 16 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_ratio: 0.1 |
|
- num_epochs: 5 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
|
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
|
| No log | 1.0 | 417 | 0.0960 | 0.7712 | 0.8074 | 0.7889 | 0.9706 | |
|
| 0.3056 | 2.0 | 834 | 0.0765 | 0.8187 | 0.8211 | 0.8199 | 0.9766 | |
|
| 0.0587 | 3.0 | 1251 | 0.0784 | 0.8116 | 0.8104 | 0.8110 | 0.9744 | |
|
| 0.0401 | 4.0 | 1668 | 0.0877 | 0.8027 | 0.8316 | 0.8169 | 0.9758 | |
|
| 0.027 | 5.0 | 2085 | 0.0924 | 0.8156 | 0.8242 | 0.8199 | 0.9768 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.44.2 |
|
- Pytorch 2.4.1+cu121 |
|
- Datasets 2.21.0 |
|
- Tokenizers 0.19.1 |
|
|
