---
license: mit
tags:
- generated_from_trainer
datasets:
- keyword_pubmed_dataset
metrics:
- accuracy
model-index:
- name: kw_pubmed_1000_0.0003
  results:
  - task:
      name: Masked Language Modeling
      type: fill-mask
    dataset:
      name: keyword_pubmed_dataset
      type: keyword_pubmed_dataset
      args: sentence
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.33938523162661094
---

<!-- 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. -->

# kw_pubmed_1000_0.0003

This model is a fine-tuned version of [microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-PubMedBERT-base-uncased-abstract-fulltext) on the keyword_pubmed_dataset dataset.
It achieves the following results on the evaluation set:
- Loss: 4.7086
- Accuracy: 0.3394

## 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: 0.0003
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 250
- total_train_batch_size: 8000
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log        | 0.09  | 4    | 4.3723          | 0.3436   |
| 6.0386        | 0.17  | 8    | 4.2113          | 0.3442   |
| 3.7573        | 0.26  | 12   | 4.2079          | 0.3634   |
| 2.9944        | 0.35  | 16   | 4.3370          | 0.3513   |
| 2.7048        | 0.44  | 20   | 4.8594          | 0.3067   |
| 2.7048        | 0.52  | 24   | 4.4929          | 0.3383   |
| 2.9458        | 0.61  | 28   | 4.5146          | 0.3408   |
| 2.3783        | 0.7   | 32   | 4.5680          | 0.3430   |
| 2.2485        | 0.78  | 36   | 4.5095          | 0.3477   |
| 2.1701        | 0.87  | 40   | 4.4971          | 0.3449   |
| 2.1701        | 0.96  | 44   | 4.7051          | 0.3321   |
| 2.0861        | 1.07  | 48   | 4.7615          | 0.3310   |
| 2.4168        | 1.15  | 52   | 4.7086          | 0.3394   |


### Framework versions

- Transformers 4.18.0
- Pytorch 1.11.0
- Datasets 2.1.0
- Tokenizers 0.12.1