Hugging Face model: Swansen1993/RepositoryBertModels
Author: Swansen1993
Created: 2026-04-22 13:51:09
Last modified: 2026-04-23 13:17:36
Pipeline: text-classification
Likes: 0 | Downloads: 0
Tags: safetensors, v1_lr2e-5_nowarmup_nodecay, text-classification, en, base_model:google-bert/bert-base-uncased, base_model:finetune:google-bert/bert-base-uncased, region:us
Base model relation: finetune
Base models: id: google-bert/bert-base-uncased
Card metadata:
language: en
base_model: google-bert/bert-base-uncased
pipeline_tag: text-classification
tags: v1_lr2e-5_nowarmup_nodecay
epochs: 3
average loss in each epoch: Average loss in epoch 1: 0.8805, Average loss in epoch 2: 0.3835, Average loss in epoch 3: 0.2537
metrics: overall accuracy: 0,876, irony, precision: 0,94, recall: 0,83, f1-score: 0,88, sample size: 131, multipolarity, precision: 0,71, recall: 0,89, f1-score: 0,79, sample size: 150, negation, precision: 0,72, recall: 0,55, f1-score: 0,63, sample size: 150, negative, precision: 0,83, recall: 0,92, f1-score: 0,87, sample size: 225, neutral, precision: 0,83, recall: 0,73, f1-score: 0,78, sample size: 150, positive, precision: 0,89, recall: 0,90, f1-score: 0,89, sample size: 225, sarcastic, precision: 0,97, recall: 0,97, f1-score: 0,97, sample size: 450
tags v2: v2_lr2e-5_nowarmup_0.01weight_decay
epochs v2: 3
average loss in each epoch v2: Average loss in epoch 1: 0.9463, Average loss in epoch 2: 0.4133, Average loss in epoch 3: 0.2684
metrics v2: overall accuracy: 0,862, irony, precision: 0,95, recall: 0,79, f1-score: 0,86, sample size: 131, multipolarity, precision: 0,73, recall: 0,91, f1-score: 0,81, sample size: 150, negation, precision: 0,67, recall: 0,49, f1-score: 0,56, sample size: 150, negative, precision: 0,82, recall: 0,92, f1-score: 0,87, sample size: 225, neutral, precision: 0,81, recall: 0,75, f1-score: 0,78, sample size: 150, positive, precision: 0,93, recall: 0,90, f1-score: 0,91, sample size: 225, sarcastic, precision: 0,95, recall: 0,98, f1-score: 0,96, sample size: 450
tags v3: v3_lr2e-5_100warmupsteps_0.01weight_decay
epochs v3: 3
average loss in each epoch v3: Average loss in epoch 1: 1.0157, Average loss in epoch 2: 0.4125, Average loss in epoch 3: 0.2722
metrics v3: overall accuracy: 0,867, irony, precision: 0,97, recall: 0,77, f1-score: 0,86, sample size: 131, multipolarity, precision: 0,72, recall: 0,91, f1-score: 0,80, sample size: 150, negation, precision: 0,73, recall: 0,56, f1-score: 0,63, sample size: 150, negative, precision: 0,83, recall: 0,94, f1-score: 0,88, sample size: 225, neutral, precision: 0,84, recall: 0,72, f1-score: 0,78, sample size: 150, positive, precision: 0,90, recall: 0,89, f1-score: 0,90, sample size: 225, sarcastic, precision: 0,95, recall: 0,98, f1-score: 0,97, sample size: 450
tags v4: v4_lr2e-5_100warmupsteps_nodecay
epochs v4: 3
average loss in each epoch v4: Average loss in epoch 1: 1.09, Average loss in epoch 2: 0.4439, Average loss in epoch 3: 0.2898
metrics v4: overall accuracy: 0,860, irony, precision: 0,96, recall: 0,79, f1-score: 0,87, sample size: 131, multipolarity, precision: 0,72, recall: 0,92, f1-score: 0,81, sample size: 150, negation, precision: 0,70, recall: 0,47, f1-score: 0,56, sample size: 150, negative, precision: 0,81, recall: 0,94, f1-score: 0,87, sample size: 225, neutral, precision: 0,79, recall: 0,73, f1-score: 0,76, sample size: 150, positive, precision: 0,92, recall: 0,89, f1-score: 0,90, sample size: 225, sarcastic, precision: 0,95, recall: 0,98, f1-score: 0,96, sample size: 450
tags v5: v5_lr4e-5_100warmupsteps_decay0.015
epochs v5: 3
average loss in each epoch v5: Average loss in epoch 1: 0.9703, Average loss in epoch 2: 0.3887, Average loss in epoch 3: 0.2168
metrics v5: overall accuracy: 0,875, irony, precision: 0,95, recall: 0,82, f1-score: 0,88, sample size: 131, multipolarity, precision: 0,75, recall: 0,89, f1-score: 0,82, sample size: 150, negation, precision: 0,777, recall: 0,59, f1-score: 0,67, sample size: 150, negative, precision: 0,85, recall: 0,95, f1-score: 0,90, sample size: 225, neutral, precision: 0,82, recall: 0,76, f1-score: 0,79, sample size: 150, positive, precision: 0,88, recall: 0,89, f1-score: 0,89, sample size: 225, sarcastic, precision: 0,96, recall: 0,97, f1-score: 0,96, sample size: 450
tags v6: v6_lr2e-5_150warmupsteps_decay0.01
epochs v6: 5
average loss in each epoch v6: Average loss in epoch 1: 1.1274, Average loss in epoch 2: 0.4649, Average loss in epoch 3: 0.2806, Average loss in epoch 4: 0.2009, Average loss in epoch 5: 0.1389
metrics v6: overall accuracy: 0,876, irony, precision: 0,97, recall: 0,82, f1-score: 0,89, sample size: 131, multipolarity, precision: 0,73, recall: 0,89, f1-score: 0,80, sample size: 150, negation, precision: 0,73, recall: 0,59, f1-score: 0,65, sample size: 150, negative, precision: 0,85, recall: 0,94, f1-score: 0,89, sample size: 225, neutral, precision: 0,84, recall: 0,75, f1-score: 0,79, sample size: 150, positive, precision: 0,91, recall: 0,90, f1-score: 0,91, sample size: 225, sarcastic, precision: 0,96, recall: 0,98, f1-score: 0,97, sample size: 450