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---
license: mit
base_model: microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: test
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. -->
# test
This model is a fine-tuned version of [microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract](https://huggingface.co/microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6886
- Accuracy: 0.8143
- F1: [0.92816572 0.56028369 0.1 0.2633452 ]
## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 10.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------------------------------------------:|
| No log | 1.0 | 37 | 0.4891 | 0.8235 | [0.91702786 0.33333333 0. 0.10837438] |
| No log | 2.0 | 74 | 0.4762 | 0.8321 | [0.93139159 0.48466258 0. 0.22857143] |
| No log | 3.0 | 111 | 0.5084 | 0.8208 | [0.92995725 0.44887781 0. 0.19266055] |
| No log | 4.0 | 148 | 0.5519 | 0.8105 | [0.92421691 0.44444444 0.06557377 0.30769231] |
| No log | 5.0 | 185 | 0.5805 | 0.8294 | [0.93531353 0.52336449 0.09345794 0.27131783] |
| No log | 6.0 | 222 | 0.6778 | 0.7955 | [0.91344509 0.55305466 0.15463918 0.29166667] |
| No log | 7.0 | 259 | 0.6407 | 0.8213 | [0.93298292 0.51383399 0.10191083 0.2519084 ] |
| No log | 8.0 | 296 | 0.6639 | 0.8272 | [0.9326288 0.55052265 0.18181818 0.26271186] |
| No log | 9.0 | 333 | 0.6863 | 0.8192 | [0.93071286 0.55830389 0.11042945 0.2761194 ] |
| No log | 10.0 | 370 | 0.6886 | 0.8143 | [0.92816572 0.56028369 0.1 0.2633452 ] |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
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