Model: tomaarsen/span-marker-bert-base-uncased-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-uncased, base_model:finetune:google-bert/bert-base-uncased, license:apache-2.0, model-index, co2_eq_emissions, region:us
Base models (finetune): id: google-bert/bert-base-uncased
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: Uncased 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: Uncased 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 te stability of models over random seeds.
example_title: Uncased 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: Uncased 4
pipeline_tag: token-classification
co2_eq_emissions: emissions: 31.203903222402037
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: 0.272
hardware_used: 1 x NVIDIA GeForce RTX 3090
base_model: bert-base-uncased
model-index: name: SpanMarker with bert-base-uncased 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: 0.9198933333333332
name: F1
verified: no, type: precision
value: 0.9339397877409573
name: Precision
verified: no, type: recall
value: 0.9062631357713324
name: Recall
verified: no
Likes: 6 | All-time downloads: 935706
Created: 2023-08-14 06:49:22