Model: tomaarsen/span-marker-bert-base-acronyms
Author: tomaarsen
Pipeline: token-classification
Library: span-marker
Tags: span-marker, pytorch, tensorboard, safetensors, token-classification, ner, named-entity-recognition, generated_from_span_marker_trainer, en, dataset:acronym_identification, base_model:google-bert/bert-base-cased, base_model:finetune:google-bert/bert-base-cased, license:apache-2.0, model-index, co2_eq_emissions, region:us
Base models (finetune): id: google-bert/bert-base-cased
Card metadata: language: en
license: apache-2.0
library_name: span-marker
tags: span-marker, token-classification, ner, named-entity-recognition, generated_from_span_marker_trainer
datasets: acronym_identification
metrics: precision, recall, f1
widget: text: Here, DA = direct assessment, RR = relative ranking, DS = discrete scale and CS = continuous scale.
example_title: Example 1, text: Modifying or replacing the Erasable Programmable Read Only Memory (EPROM) in a phone would allow the configuration of any ESN and MIN via software for cellular devices.
example_title: Example 2, text: We propose a technique called Aggressive Stochastic Weight Averaging (ASWA) and an extension called Norm-filtered Aggressive Stochastic Weight Averaging (NASWA) which improves the stability of models over random seeds.
example_title: Example 3, text: The choice of the encoder and decoder modules of DNPG can be quite flexible, for instance long-short term memory networks (LSTM) or convolutional neural network (CNN).
example_title: Example 4
pipeline_tag: token-classification
co2_eq_emissions: emissions: 30.818996419923273
source: codecarbon
training_type: fine-tuning
on_cloud: no
cpu_model: 13th Gen Intel(R) Core(TM) i7-13700K
ram_total_size: 31.777088165283203
hours_used: 0.204
hardware_used: 1 x NVIDIA GeForce RTX 3090
base_model: bert-base-cased
model-index: name: SpanMarker with bert-base-cased on Acronym Identification
results: task: type: token-classification
name: Named Entity Recognition
dataset: name: Acronym Identification
type: acronym_identification
split: validation
metrics: type: f1
value: 0.9336161187698834
name: F1
verified: no, type: precision
value: 0.942208904109589
name: Precision
verified: no, type: recall
value: 0.9251786464901219
name: Recall
verified: no
Likes: 7 | All-time downloads: 24210
Created: 2023-08-13 22:25:04