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+*.spm filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,336 @@
+---
+language:
+- bs
+- en
+- hr
+- sh
+- sr
+language_bcp47:
+- bs_Latn
+- sr_Cyrl
+- sr_Latn
+
+tags:
+- translation
+- opus-mt-tc
+
+license: cc-by-4.0
+model-index:
+- name: opus-mt-tc-base-en-sh
+  results:
+  - task:
+      name: Translation eng-hrv
+      type: translation
+      args: eng-hrv
+    dataset:
+      name: flores200-dev
+      type: flores200-dev
+      args: eng-hrv
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 28.1
+       - name: chr-F
+         type: chrf
+         value: 0.57963
+  - task:
+      name: Translation eng-srp_Cyrl
+      type: translation
+      args: eng-srp_Cyrl
+    dataset:
+      name: flores200-dev
+      type: flores200-dev
+      args: eng-srp_Cyrl
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 32.2
+       - name: chr-F
+         type: chrf
+         value: 0.60096
+  - task:
+      name: Translation eng-hrv
+      type: translation
+      args: eng-hrv
+    dataset:
+      name: flores200-devtest
+      type: flores200-devtest
+      args: eng-hrv
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 28.9
+       - name: chr-F
+         type: chrf
+         value: 0.58652
+  - task:
+      name: Translation eng-srp_Cyrl
+      type: translation
+      args: eng-srp_Cyrl
+    dataset:
+      name: flores200-devtest
+      type: flores200-devtest
+      args: eng-srp_Cyrl
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 31.7
+       - name: chr-F
+         type: chrf
+         value: 0.59874
+  - task:
+      name: Translation eng-hrv
+      type: translation
+      args: eng-hrv
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: eng hrv devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 28.7
+       - name: chr-F
+         type: chrf
+         value: 0.586
+  - task:
+      name: Translation eng-srp_Cyrl
+      type: translation
+      args: eng-srp_Cyrl
+    dataset:
+      name: flores101-devtest
+      type: flores_101
+      args: eng srp_Cyrl devtest
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 31.7
+       - name: chr-F
+         type: chrf
+         value: 0.59874
+  - task:
+      name: Translation eng-bos_Latn
+      type: translation
+      args: eng-bos_Latn
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: eng-bos_Latn
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 46.3
+       - name: chr-F
+         type: chrf
+         value: 0.666
+  - task:
+      name: Translation eng-hbs
+      type: translation
+      args: eng-hbs
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: eng-hbs
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 42.1
+       - name: chr-F
+         type: chrf
+         value: 0.631
+  - task:
+      name: Translation eng-hrv
+      type: translation
+      args: eng-hrv
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: eng-hrv
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 49.7
+       - name: chr-F
+         type: chrf
+         value: 0.691
+  - task:
+      name: Translation eng-srp_Cyrl
+      type: translation
+      args: eng-srp_Cyrl
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: eng-srp_Cyrl
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 45.1
+       - name: chr-F
+         type: chrf
+         value: 0.645
+  - task:
+      name: Translation eng-srp_Latn
+      type: translation
+      args: eng-srp_Latn
+    dataset:
+      name: tatoeba-test-v2021-08-07
+      type: tatoeba_mt
+      args: eng-srp_Latn
+    metrics:
+       - name: BLEU
+         type: bleu
+         value: 39.8
+       - name: chr-F
+         type: chrf
+         value: 0.613
+---
+# opus-mt-tc-base-en-sh
+
+## Table of Contents
+- [Model Details](#model-details)
+- [Uses](#uses)
+- [Risks, Limitations and Biases](#risks-limitations-and-biases)
+- [How to Get Started With the Model](#how-to-get-started-with-the-model)
+- [Training](#training)
+- [Evaluation](#evaluation)
+- [Citation Information](#citation-information)
+- [Acknowledgements](#acknowledgements)
+
+## Model Details
+
+Neural machine translation model for translating from English (en) to Serbo-Croatian (sh).
+
+This model is part of the [OPUS-MT project](https://github.com/Helsinki-NLP/Opus-MT), an effort to make neural machine translation models widely available and accessible for many languages in the world. All models are originally trained using the amazing framework of [Marian NMT](https://marian-nmt.github.io/), an efficient NMT implementation written in pure C++. The models have been converted to pyTorch using the transformers library by huggingface. Training data is taken from [OPUS](https://opus.nlpl.eu/) and training pipelines use the procedures of [OPUS-MT-train](https://github.com/Helsinki-NLP/Opus-MT-train).
+**Model Description:**
+- **Developed by:** Language Technology Research Group at the University of Helsinki
+- **Model Type:** Translation (transformer-align)
+- **Release**: 2021-04-20
+- **License:** CC-BY-4.0
+- **Language(s):**  
+  - Source Language(s): eng
+  - Target Language(s): bos_Latn hbs hrv srp_Cyrl srp_Latn
+  - Language Pair(s): eng-bos_Latn eng-hbs eng-hrv eng-srp_Cyrl eng-srp_Latn
+  - Valid Target Language Labels: >>bos_Cyrl<< >>bos_Latn<< >>cnr<< >>cnr_Latn<< >>hbs<< >>hbs_Cyrl<< >>hrv<< >>srp_Cyrl<< >>srp_Latn<<
+- **Original Model**: [opus+bt-2021-04-20.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-hbs/opus+bt-2021-04-20.zip)
+- **Resources for more information:**
+  - [OPUS-MT-train GitHub Repo](https://github.com/Helsinki-NLP/OPUS-MT-train)
+  - More information about released models for this language pair: [OPUS-MT eng-hbs README](https://github.com/Helsinki-NLP/Tatoeba-Challenge/tree/master/models/eng-hbs/README.md)
+  - [More information about MarianNMT models in the transformers library](https://huggingface.co/docs/transformers/model_doc/marian)
+  - [Tatoeba Translation Challenge](https://github.com/Helsinki-NLP/Tatoeba-Challenge/
+
+This is a multilingual translation model with multiple target languages. A sentence initial language token is required in the form of `>>id<<` (id = valid target language ID), e.g. `>>bos_Latn<<`
+
+## Uses
+
+This model can be used for translation and text-to-text generation.
+
+## Risks, Limitations and Biases
+
+**CONTENT WARNING: Readers should be aware that the model is trained on various public data sets that may contain content that is disturbing, offensive, and can propagate historical and current stereotypes.**
+
+Significant research has explored bias and fairness issues with language models (see, e.g., [Sheng et al. (2021)](https://aclanthology.org/2021.acl-long.330.pdf) and [Bender et al. (2021)](https://dl.acm.org/doi/pdf/10.1145/3442188.3445922)).
+
+## How to Get Started With the Model
+
+A short example code:
+
+```python
+from transformers import MarianMTModel, MarianTokenizer
+
+src_text = [
+    ">>hrv<< You're about to make a very serious mistake.",
+    ">>hbs<< I've just been too busy."
+]
+
+model_name = "pytorch-models/opus-mt-tc-base-en-sh"
+tokenizer = MarianTokenizer.from_pretrained(model_name)
+model = MarianMTModel.from_pretrained(model_name)
+translated = model.generate(**tokenizer(src_text, return_tensors="pt", padding=True))
+
+for t in translated:
+    print( tokenizer.decode(t, skip_special_tokens=True) )
+
+# expected output:
+#     Ti si o tome napraviti vrlo ozbiljnu pogrešku.
+#     [4]
+```
+
+You can also use OPUS-MT models with the transformers pipelines, for example:
+
+```python
+from transformers import pipeline
+pipe = pipeline("translation", model="Helsinki-NLP/opus-mt-tc-base-en-sh")
+print(pipe(">>hrv<< You're about to make a very serious mistake."))
+
+# expected output: Ti si o tome napraviti vrlo ozbiljnu pogrešku.
+```
+
+## Training
+
+- **Data**: opus+bt ([source](https://github.com/Helsinki-NLP/Tatoeba-Challenge))
+- **Pre-processing**: SentencePiece (spm32k,spm32k)
+- **Model Type:**  transformer-align
+- **Original MarianNMT Model**: [opus+bt-2021-04-20.zip](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-hbs/opus+bt-2021-04-20.zip)
+- **Training Scripts**: [GitHub Repo](https://github.com/Helsinki-NLP/OPUS-MT-train)
+
+## Evaluation
+
+* test set translations: [opus+bt-2021-04-20.test.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-hbs/opus+bt-2021-04-20.test.txt)
+* test set scores: [opus+bt-2021-04-20.eval.txt](https://object.pouta.csc.fi/Tatoeba-MT-models/eng-hbs/opus+bt-2021-04-20.eval.txt)
+* benchmark results: [benchmark_results.txt](benchmark_results.txt)
+* benchmark output: [benchmark_translations.zip](benchmark_translations.zip)
+
+| langpair | testset | chr-F | BLEU  | #sent | #words |
+|----------|---------|-------|-------|-------|--------|
+| eng-bos_Latn | tatoeba-test-v2021-08-07 | 0.666 | 46.3 | 301 | 1650 |
+| eng-hbs | tatoeba-test-v2021-08-07 | 0.631 | 42.1 | 10017 | 63927 |
+| eng-hrv | tatoeba-test-v2021-08-07 | 0.691 | 49.7 | 1480 | 9396 |
+| eng-srp_Cyrl | tatoeba-test-v2021-08-07 | 0.645 | 45.1 | 1580 | 9152 |
+| eng-srp_Latn | tatoeba-test-v2021-08-07 | 0.613 | 39.8 | 6656 | 43729 |
+| eng-hrv | flores101-devtest | 0.586 | 28.7 | 1012 | 22423 |
+| eng-hrv | flores200-dev | 0.57963 | 28.1 | 997 | 21567 |
+| eng-hrv | flores200-devtest | 0.58652 | 28.9 | 1012 | 22423 |
+| eng-srp_Cyrl | flores101-devtest | 0.59874 | 31.7 | 1012 | 23456 |
+| eng-srp_Cyrl | flores200-dev | 0.60096 | 32.2 | 997 | 22384 |
+| eng-srp_Cyrl | flores200-devtest | 0.59874 | 31.7 | 1012 | 23456 |
+
+## Citation Information
+
+* Publications: [OPUS-MT – Building open translation services for the World](https://aclanthology.org/2020.eamt-1.61/) and [The Tatoeba Translation Challenge – Realistic Data Sets for Low Resource and Multilingual MT](https://aclanthology.org/2020.wmt-1.139/) (Please, cite if you use this model.)
+
+```
+@inproceedings{tiedemann-thottingal-2020-opus,
+    title = "{OPUS}-{MT} {--} Building open translation services for the World",
+    author = {Tiedemann, J{\"o}rg  and Thottingal, Santhosh},
+    booktitle = "Proceedings of the 22nd Annual Conference of the European Association for Machine Translation",
+    month = nov,
+    year = "2020",
+    address = "Lisboa, Portugal",
+    publisher = "European Association for Machine Translation",
+    url = "https://aclanthology.org/2020.eamt-1.61",
+    pages = "479--480",
+}
+
+@inproceedings{tiedemann-2020-tatoeba,
+    title = "The Tatoeba Translation Challenge {--} Realistic Data Sets for Low Resource and Multilingual {MT}",
+    author = {Tiedemann, J{\"o}rg},
+    booktitle = "Proceedings of the Fifth Conference on Machine Translation",
+    month = nov,
+    year = "2020",
+    address = "Online",
+    publisher = "Association for Computational Linguistics",
+    url = "https://aclanthology.org/2020.wmt-1.139",
+    pages = "1174--1182",
+}
+```
+
+## Acknowledgements
+
+The work is supported by the [European Language Grid](https://www.european-language-grid.eu/) as [pilot project 2866](https://live.european-language-grid.eu/catalogue/#/resource/projects/2866), by the [FoTran project](https://www.helsinki.fi/en/researchgroups/natural-language-understanding-with-cross-lingual-grounding), funded by the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 771113), and the [MeMAD project](https://memad.eu/), funded by the European Union’s Horizon 2020 Research and Innovation Programme under grant agreement No 780069. We are also grateful for the generous computational resources and IT infrastructure provided by [CSC -- IT Center for Science](https://www.csc.fi/), Finland.
+
+## Model conversion info
+
+* transformers version: 4.16.2
+* OPUS-MT git hash: e2a6299
+* port time: Tue Oct 11 10:14:32 CEST 2022
+* port machine: LM0-400-22516.local

benchmark_results.txt

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+eng-bos_Latn	tatoeba-test-v2020-07-28	0.667	46.4	300	1647
+eng-bos_Latn	tatoeba-test-v2021-03-30	0.667	46.4	300	1647
+eng-bos_Latn	tatoeba-test-v2021-08-07	0.666	46.3	301	1650
+eng-hbs	tatoeba-test-v2020-07-28	0.630	42.1	10000	63836
+eng-hbs	tatoeba-test-v2021-03-30	0.630	42.1	10002	63845
+eng-hbs	tatoeba-test-v2021-08-07	0.631	42.1	10017	63927
+eng-hrv	flores101-dev	0.580	28.2	997	21567
+eng-hrv	flores101-devtest	0.586	28.7	1012	22423
+eng-hrv	flores200-dev	0.57963	28.1	997	21567
+eng-hrv	flores200-devtest	0.58652	28.9	1012	22423
+eng-hrv	tatoeba-test-v2020-07-28	0.690	49.6	1468	9332
+eng-hrv	tatoeba-test-v2021-03-30	0.691	49.7	1469	9336
+eng-hrv	tatoeba-test-v2021-08-07	0.691	49.7	1480	9396
+eng-srp_Cyrl	flores101-dev	0.60096	32.2	997	22384
+eng-srp_Cyrl	flores101-devtest	0.59874	31.7	1012	23456
+eng-srp_Cyrl	flores200-dev	0.60096	32.2	997	22384
+eng-srp_Cyrl	flores200-devtest	0.59874	31.7	1012	23456
+eng-srp_Cyrl	tatoeba-test-v2020-07-28	0.644	44.9	1577	9133
+eng-srp_Cyrl	tatoeba-test-v2021-03-30	0.644	44.9	1577	9133
+eng-srp_Cyrl	tatoeba-test-v2021-08-07	0.645	45.1	1580	9152
+eng-srp_Latn	tatoeba-test-v2020-07-28	0.613	39.7	6655	43724
+eng-srp_Latn	tatoeba-test-v2021-03-30	0.613	39.7	6656	43729
+eng-srp_Latn	tatoeba-test-v2021-08-07	0.613	39.8	6656	43729

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+  "scale_embedding": true,
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+  "static_position_embeddings": true,
+  "torch_dtype": "float16",
+  "transformers_version": "4.18.0.dev0",
+  "use_cache": true,
+  "vocab_size": 58639
+}

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