Add PhilTa files
Browse files- README.md +53 -0
- config.json +28 -0
- flax_model.msgpack +3 -0
- pytorch_model.bin +3 -0
- special_tokens_map.json +107 -0
- tokenizer.json +0 -0
- tokenizer_config.json +111 -0
README.md
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---
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language:
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- multilingual
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- grc
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- en
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- la
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license: apache-2.0
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inference: false
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---
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# PhilTa
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The paper [Exploring Language Models for Classical Philology](https://todo.com) is the first effort to systematically provide state-of-the-art language models for Classical Philology. PhilTa is a T5-base sized, multilingual, encoder-decoder variant.
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This model was trained using data from the [Open Greek & Latin Project](https://opengreekandlatin.org/), the CLARIN corpus [Greek Medieval Texts](https://inventory.clarin.gr/corpus/890), the [Patrologia Graeca](https://patristica.net/graeca/), the [Corpus Corporum](https://mlat.uzh.ch/), and [Project Gutenberg](https://www.gutenberg.org/).
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Further information can be found in our paper or in our [GitHub repository](https://github.com/Heidelberg-NLP/ancient-language-models).
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## Usage
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```python
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from transformers import AutoTokenizer, AutoModelForConditionalGeneration
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tokenizer = AutoTokenizer.from_pretrained('bowphs/PhilTa')
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model = AutoModelForConditionalGeneration.from_pretrained('bowphs/PhilTa')
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```
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Please check out the awesome Hugging Face tutorials on how to fine-tune our models.
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## Evaluation Results
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When fine-tuned on lemmatization data from [EvaLatin 2022](https://universaldependencies.org/), PhilTa achieves the following results:
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| Task | Classical | Cross-genre | Cross-time |
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|:--:|:--:|:--:|:--:|
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| |97.33|93.40|91.91|
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PhilTa is especially strong when more than one of the three languages should be processed.
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## Contact
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If you have any questions or problems, feel free to [reach out](mailto:riemenschneider@cl.uni-heidelberg.de).
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## Citation
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```bibtex
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@incollection{riemenschneiderfrank:2023,
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address = "Toronto, Canada",
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author = "Riemenschneider, Frederick and Frank, Anette",
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booktitle = "Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (ACL’23)",
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note = "to appear",
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pubType = "incollection",
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publisher = "Association for Computational Linguistics",
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title = "Exploring Large Language Models for Classical Philology",
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url = "https://arxiv.org/abs/2305.13698",
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year = "2023",
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key = "riemenschneiderfrank:2023"
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}
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```
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config.json
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{
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"_name_or_path": "bowphs/PhilTa",
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"architectures": [
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"T5ForConditionalGeneration"
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],
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"d_ff": 2048,
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"d_kv": 64,
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"d_model": 768,
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"decoder_start_token_id": 0,
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"dropout_rate": 0.1,
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"eos_token_id": 1,
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"feed_forward_proj": "gated-gelu",
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"gradient_checkpointing": false,
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"initializer_factor": 1.0,
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"is_encoder_decoder": true,
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"layer_norm_epsilon": 1e-06,
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"model_type": "t5",
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"num_decoder_layers": 12,
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"num_heads": 12,
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"num_layers": 12,
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"output_past": true,
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"pad_token_id": 0,
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"relative_attention_num_buckets": 32,
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"tie_word_embeddings": false,
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"transformers_version": "4.10.0",
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"use_cache": true,
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"vocab_size": 64103
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}
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flax_model.msgpack
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version https://git-lfs.github.com/spec/v1
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oid sha256:73ec372068fc4aec5d49b6e38ae8382f88368506c205f4d760ae6f0ccb3c88a3
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size 1186778015
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pytorch_model.bin
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version https://git-lfs.github.com/spec/v1
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oid sha256:609ad98260da478bf53f8e0298df1eb75595c96494c11444c9f278b7460e7cf9
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size 1186857037
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special_tokens_map.json
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{
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tokenizer.json
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tokenizer_config.json
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|
98 |
+
"<extra_id_95>",
|
99 |
+
"<extra_id_96>",
|
100 |
+
"<extra_id_97>",
|
101 |
+
"<extra_id_98>",
|
102 |
+
"<extra_id_99>"
|
103 |
+
],
|
104 |
+
"eos_token": "</s>",
|
105 |
+
"extra_ids": 100,
|
106 |
+
"name_or_path": "bowphs/t5-homer",
|
107 |
+
"pad_token": "<pad>",
|
108 |
+
"special_tokens_map_file": null,
|
109 |
+
"tokenizer_class": "T5Tokenizer",
|
110 |
+
"unk_token": "<unk>"
|
111 |
+
}
|