Full models v2.0
Browse files- .gitattributes +3 -0
- README.md +18 -0
- config.json +30 -0
- metadata.yaml +29 -0
- model.en-he.en +3 -0
- model.en-he.he +3 -0
- sentencepiece.bpe.model +3 -0
- special_tokens_map.json +15 -0
- tf_model.h5 +3 -0
- tokenizer.json +3 -0
- tokenizer_config.json +21 -0
.gitattributes
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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*.zip filter=lfs diff=lfs merge=lfs -text
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*.zst filter=lfs diff=lfs merge=lfs -text
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*tfevents* filter=lfs diff=lfs merge=lfs -text
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lm.* filter=lfs diff=lfs merge=lfs -text
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model.??-??.?? filter=lfs diff=lfs merge=lfs -text
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tokenizer.json filter=lfs diff=lfs merge=lfs -text
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README.md
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---
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language:
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- en
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- he
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- multilingual
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license: cc-by-sa-4.0
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tags:
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- bicleaner-ai
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tasks:
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- text-classification
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---
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# Bicleaner AI full model for en-he
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Bicleaner AI is a tool that aims at detecting noisy sentence pairs in a parallel corpus. It
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indicates the likelihood of a pair of sentences being mutual translations (with a value near to 1) or not (with a value near to 0).
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Sentence pairs considered very noisy are scored with 0.
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Find out at our repository for further instructions on how to use it: https://github.com/bitextor/bicleaner-ai
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config.json
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{
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"_name_or_path": "bitextor/bicleaner-ai-full-en-he",
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"architectures": [
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"XLMRBicleanerAI"
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],
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"attention_probs_dropout_prob": 0.1,
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"bos_token_id": 0,
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"classifier_dropout": null,
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"eos_token_id": 2,
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"head_activation": "relu",
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"head_dropout": 0.1,
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"head_hidden_size": 2048,
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"hidden_act": "gelu",
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"hidden_dropout_prob": 0.1,
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"hidden_size": 768,
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"initializer_range": 0.02,
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"intermediate_size": 3072,
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"layer_norm_eps": 1e-05,
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"max_position_embeddings": 514,
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"model_type": "xlm-roberta",
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"num_attention_heads": 12,
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"num_hidden_layers": 12,
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"output_past": true,
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"pad_token_id": 1,
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"position_embedding_type": "absolute",
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"transformers_version": "4.26.0",
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"type_vocab_size": 1,
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"use_cache": true,
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"vocab_size": 250002
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}
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metadata.yaml
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bicleaner_ai_version: 2.1.1
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precision_score: 0.792
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recall_score: 0.883
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f1_score: 0.835
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matthews_corr_coef: 0.816
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source_lang: en
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target_lang: he
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source_lm: model.en-he.en
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target_lm: model.en-he.he
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lm_type: CHARACTER
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clean_mean_perp: -1.1462711341492502
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clean_stddev_perp: 0.16328577116648196
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noisy_mean_perp: -4.026560897183207
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noisy_stddev_perp: 0.17240383371354484
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classifier_type: xlmr
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classifier_settings:
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activation: relu
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base_model: jplu/tf-xlm-roberta-base
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batch_size: 96
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calibration_params: [7.69217110, -2.88974404]
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epochs: 15
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loss: binary_crossentropy
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maxlen: 150
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model_name: bitextor/bicleaner-ai-full-en-he
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n_classes: 2
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n_hidden: 2048
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patience: 3
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steps_per_epoch: 2000
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warmup_steps: 1000
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model.en-he.en
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version https://git-lfs.github.com/spec/v1
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oid sha256:afbaadd66881d23f2c1a308c99e9b688478ba5d722b8c6da644e3af52c331177
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size 104627359
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model.en-he.he
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version https://git-lfs.github.com/spec/v1
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oid sha256:fc3ff0a7cd2381fb9269dc9cf0faa8f3e1ad8e519a2a62acd587ea980562301b
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size 204505029
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sentencepiece.bpe.model
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version https://git-lfs.github.com/spec/v1
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oid sha256:cfc8146abe2a0488e9e2a0c56de7952f7c11ab059eca145a0a727afce0db2865
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size 5069051
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special_tokens_map.json
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{
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"bos_token": "<s>",
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"cls_token": "<s>",
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"eos_token": "</s>",
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"mask_token": {
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"content": "<mask>",
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"lstrip": true,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"pad_token": "<pad>",
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"sep_token": "</s>",
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"unk_token": "<unk>"
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}
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tf_model.h5
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version https://git-lfs.github.com/spec/v1
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oid sha256:a127869c5a61dc270ed0e25fae2026e8e56b45fffdc4466f663a263dac50180d
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size 1116401472
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tokenizer.json
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version https://git-lfs.github.com/spec/v1
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oid sha256:672b5602c725cafd47011e4e49d4b211fd746d0de2e8e187549f0324685987d0
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size 17098332
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tokenizer_config.json
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{
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"bos_token": "<s>",
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"cls_token": "<s>",
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"eos_token": "</s>",
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"mask_token": {
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"__type": "AddedToken",
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"content": "<mask>",
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"lstrip": true,
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"normalized": true,
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"rstrip": false,
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"single_word": false
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},
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"model_max_length": 1000000000000000019884624838656,
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"name_or_path": "jplu/tf-xlm-roberta-base",
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"pad_token": "<pad>",
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"sep_token": "</s>",
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"sp_model_kwargs": {},
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"special_tokens_map_file": null,
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"tokenizer_class": "XLMRobertaTokenizer",
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"unk_token": "<unk>"
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}
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