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---
base_model: microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext
library_name: transformers
license: mit
pipeline_tag: text-classification
tags:
- generated_from_trainer
model-index:
- name: pombe_curation_fold_0
results:
- task:
type: text-classification
name: Text Classification
dataset:
name: afg1/pombe-canto-data
type: text-classification
split: test
metrics:
- type: accuracy
value: 0.9254826254826255
name: Accuracy
- type: recall
value: 0.9372056514913658
name: Recall
- type: precision
value: 0.9135424636572304
name: Precision
- type: f1
value: 0.9252227818674932
name: F1
- type: total_time_in_seconds
value: 118.32597812499444
name: Total_Time_In_Seconds
- type: samples_per_second
value: 21.88868447184131
name: Samples_Per_Second
- type: latency_in_seconds
value: 0.04568570583976619
name: Latency_In_Seconds
---
<!-- 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. -->
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/afg1/pombe_curation_model/runs/richbds0)
# pombe_curation_fold_0
This model is a fine-tuned version of [microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext](https://huggingface.co/microsoft/BiomedNLP-BiomedBERT-base-uncased-abstract-fulltext) on an unknown dataset.
## 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: 32
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1.0
- mixed_precision_training: Native AMP
### Framework versions
- Transformers 4.42.3
- Pytorch 2.2.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1 |