metadata
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: bert-base-uncased-issues-128
results: []
bert-base-uncased-issues-128
This model is a fine-tuned version of bert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.2512
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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 16
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 2.1019 | 1.0 | 291 | 1.7019 |
| 1.6412 | 2.0 | 582 | 1.4273 |
| 1.4844 | 3.0 | 873 | 1.3947 |
| 1.4006 | 4.0 | 1164 | 1.3698 |
| 1.3382 | 5.0 | 1455 | 1.1941 |
| 1.2822 | 6.0 | 1746 | 1.2781 |
| 1.2393 | 7.0 | 2037 | 1.2650 |
| 1.2009 | 8.0 | 2328 | 1.2082 |
| 1.1657 | 9.0 | 2619 | 1.1776 |
| 1.1394 | 10.0 | 2910 | 1.2050 |
| 1.1276 | 11.0 | 3201 | 1.2067 |
| 1.1051 | 12.0 | 3492 | 1.1630 |
| 1.0814 | 13.0 | 3783 | 1.2529 |
| 1.0757 | 14.0 | 4074 | 1.1699 |
| 1.063 | 15.0 | 4365 | 1.1113 |
| 1.0637 | 16.0 | 4656 | 1.2512 |
Framework versions
- Transformers 4.11.3
- Pytorch 1.11.0+cu113
- Datasets 1.16.1
- Tokenizers 0.10.1
Model Recycling
Evaluation on 36 datasets using jmassot/bert-base-uncased-issues-128 as a base model yields average score of 73.70 in comparison to 72.20 by bert-base-uncased.
The model is ranked 3rd among all tested models for the bert-base-uncased architecture as of 21/12/2022 Results:
| 20_newsgroup | ag_news | amazon_reviews_multi | anli | boolq | cb | cola | copa | dbpedia | esnli | financial_phrasebank | imdb | isear | mnli | mrpc | multirc | poem_sentiment | qnli | qqp | rotten_tomatoes | rte | sst2 | sst_5bins | stsb | trec_coarse | trec_fine | tweet_ev_emoji | tweet_ev_emotion | tweet_ev_hate | tweet_ev_irony | tweet_ev_offensive | tweet_ev_sentiment | wic | wnli | wsc | yahoo_answers |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 84.2007 | 89.7333 | 65.86 | 47.75 | 71.4679 | 71.4286 | 82.6462 | 59 | 78.6 | 90.34 | 79.5 | 91.432 | 69.0352 | 83.5639 | 83.3333 | 61.2005 | 67.3077 | 90.4082 | 89.7353 | 85.272 | 64.6209 | 91.9725 | 52.8054 | 86.4351 | 96.6 | 77 | 36.41 | 80.3659 | 53.0303 | 66.9643 | 85.1163 | 70.0179 | 62.3824 | 52.1127 | 63.4615 | 72 |
For more information, see: Model Recycling