transformers_issues_topics
This is a BERTopic model. BERTopic is a flexible and modular topic modeling framework that allows for the generation of easily interpretable topics from large datasets.
Usage
To use this model, please install BERTopic:
pip install -U bertopic
You can use the model as follows:
from bertopic import BERTopic
topic_model = BERTopic.load("FlorenceAndTheMachine/transformers_issues_topics")
topic_model.get_topic_info()
Topic overview
- Number of topics: 30
- Number of training documents: 9000
<details> <summary>Click here for an overview of all topics.</summary>
| Topic ID | Topic Keywords | Topic Frequency | Label |
|---|---|---|---|
| -1 | bert - tensorflow - pretrained - model - pytorch | 14 | -1_bert_tensorflow_pretrained_model |
| 0 | bertforsequenceclassification - bart - t5 - tokenizers - tokenizer | 2023 | 0_bertforsequenceclassification_bart_t5_tokenizers |
| 1 | trainertrain - trainer - pretrained - frompretrained - training | 1809 | 1_trainertrain_trainer_pretrained_frompretrained |
| 2 | s2s - seq2seqtrainer - seq2seq - examplesseq2seq - runseq2seqpy | 1258 | 2_s2s_seq2seqtrainer_seq2seq_examplesseq2seq |
| 3 | modelcard - modelcards - card - model - cards | 603 | 3_modelcard_modelcards_card_model |
| 4 | attributeerror - typeerror - valueerror - error - runmlmpy | 410 | 4_attributeerror_typeerror_valueerror_error |
| 5 | xlnet - xlnetmodel - xlnetlmheadmodel - xlarge - xlm | 360 | 5_xlnet_xlnetmodel_xlnetlmheadmodel_xlarge |
| 6 | gpt2 - gpt2tokenizer - gpt2xl - gpt2tokenizerfast - gpt | 289 | 6_gpt2_gpt2tokenizer_gpt2xl_gpt2tokenizerfast |
| 7 | readmemd - readmetxt - readme - file - camembertbasereadmemd | 279 | 7_readmemd_readmetxt_readme_file |
| 8 | typos - typo - fix - correction - fixed | 261 | 8_typos_typo_fix_correction |
| 9 | transformerscli - transformers - transformer - transformerxl - importerror | 245 | 9_transformerscli_transformers_transformer_transformerxl |
| 10 | ner - pipeline - pipelines - nerpipeline - fillmaskpipeline | 199 | 10_ner_pipeline_pipelines_nerpipeline |
| 11 | glue - gluepy - glueconvertexamplestofeatures - huggingfacetransformers - huggingfacemaster | 160 | 11_glue_gluepy_glueconvertexamplestofeatures_huggingfacetransformers |
| 12 | questionansweringpipeline - questionanswering - answering - tfalbertforquestionanswering - distilbertforquestionanswering | 157 | 12_questionansweringpipeline_questionanswering_answering_tfalbertforquestionanswering |
| 13 | logging - logs - log - onlog - logger | 136 | 13_logging_logs_log_onlog |
| 14 | onnx - onnxonnxruntime - onnxexport - 04onnxexport - 04onnxexportipynb | 130 | 14_onnx_onnxonnxruntime_onnxexport_04onnxexport |
| 15 | benchmark - benchmarks - accuracy - evaluation - metrics | 86 | 15_benchmark_benchmarks_accuracy_evaluation |
| 16 | labelsmoothednllloss - labelsmoothingfactor - label - labels - labelsmoothing | 84 | 16_labelsmoothednllloss_labelsmoothingfactor_label_labels |
| 17 | longformer - longformers - longform - longformerforqa - longformerlayer | 83 | 17_longformer_longformers_longform_longformerforqa |
| 18 | generationbeamsearchpy - generatebeamsearch - generatebeamsearchoutputs - beamsearch - nonbeamsearch | 77 | 18_generationbeamsearchpy_generatebeamsearch_generatebeamsearchoutputs_beamsearch |
| 19 | wav2vec2 - wav2vec - wav2vec20 - wav2vec2forctc - wav2vec2xlrswav2vec2 | 60 | 19_wav2vec2_wav2vec_wav2vec20_wav2vec2forctc |
| 20 | flax - flaxelectraformaskedlm - flaxelectraforpretraining - flaxjax - flaxelectramodel | 48 | 20_flax_flaxelectraformaskedlm_flaxelectraforpretraining_flaxjax |
| 21 | cachedir - cache - cachedpath - caching - cached | 42 | 21_cachedir_cache_cachedpath_caching |
| 22 | notebook - notebooks - community - sagemakertrainer - documentation | 37 | 22_notebook_notebooks_community_sagemakertrainer |
| 23 | wandbproject - wandb - wandbcallback - wandbdisabled - wandbdisabledtrue | 34 | 23_wandbproject_wandb_wandbcallback_wandbdisabled |
| 24 | add - bort - added - py7zr - update | 33 | 24_add_bort_added_py7zr |
| 25 | electra - electraformaskedlm - electraformultiplechoice - electrafortokenclassification - electraforsequenceclassification | 30 | 25_electra_electraformaskedlm_electraformultiplechoice_electrafortokenclassification |
| 26 | layoutlm - layout - layoutlmtokenizer - layoutlmbaseuncased - tf | 19 | 26_layoutlm_layout_layoutlmtokenizer_layoutlmbaseuncased |
| 27 | isort - blackisortflake8 - dependencies - github - matplotlib | 17 | 27_isort_blackisortflake8_dependencies_github |
| 28 | pplm - pr - deprecated - variable - ppl | 17 | 28_pplm_pr_deprecated_variable |
</details>
Training hyperparameters
- calculate_probabilities: False
- language: english
- low_memory: False
- min_topic_size: 10
- n_gram_range: (1, 1)
- nr_topics: 30
- seed_topic_list: None
- top_n_words: 10
- verbose: True
Framework versions
- Numpy: 1.23.5
- HDBSCAN: 0.8.33
- UMAP: 0.5.3
- Pandas: 1.5.3
- Scikit-Learn: 1.2.2
- Sentence-transformers: 2.2.2
- Transformers: 4.33.0
- Numba: 0.56.4
- Plotly: 5.15.0
- Python: 3.10.12
