add model

README.md

@@ -1,67 +1,47 @@
 ---
-datasets:
-- ctu-aic/csfever
-- xnli
-languages:
-- cs
-license: cc-by-sa-4.0
 tags:
-- natural-language-inference
-
+- generated_from_keras_callback
+model-index:
+- name: xlm-roberta-large-xnli-csfever
+  results: []
 ---
 
-# 🦾 xlm-roberta-large-xnli-csfever
-
-## 🧰 Usage
-
-### 🤗 Using Huggingface `transformers`
-```python
-from transformers import AutoModelForSequenceClassification, AutoTokenizer
-model = AutoModelForSequenceClassification.from_pretrained("ctu-aic/xlm-roberta-large-xnli-csfever")
-tokenizer = AutoTokenizer.from_pretrained("ctu-aic/xlm-roberta-large-xnli-csfever")
-```
-
-### 👾 Using UKPLab `sentence_transformers` `CrossEncoder`
-The model was trained using the `CrossEncoder` API and we recommend it for its usage.
-```python
-from sentence_transformers.cross_encoder import CrossEncoder
-model = CrossEncoder('ctu-aic/xlm-roberta-large-xnli-csfever')
-scores = model.predict([["My first context.", "My first hypothesis."],  
-                        ["Second context.", "Hypothesis."]])
-```
-
-## 🌳 Contributing
-Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
-
-## 👬 Authors
-The model was trained and uploaded by **[ullriher](https://udb.fel.cvut.cz/?uid=ullriher&sn=&givenname=&_cmd=Hledat&_reqn=1&_type=user&setlang=en)** (e-mail: [ullriher@fel.cvut.cz](mailto:ullriher@fel.cvut.cz))
-
-The code was codeveloped by the NLP team at Artificial Intelligence Center of CTU in Prague ([AIC](https://www.aic.fel.cvut.cz/)).
-
-## 🔐 License
-[cc-by-sa-4.0](https://choosealicense.com/licenses/cc-by-sa-4.0)
-
-## 💬 Citation
-If you find this model helpful, feel free to cite our publication:
-```
-
-@article{DBLP:journals/corr/abs-2201-11115,
-  author    = {Jan Drchal and
-               Herbert Ullrich and
-               Martin R{'{y}}par and
-               Hana Vincourov{'{a}} and
-               V{'{a}}clav Moravec},
-  title     = {CsFEVER and CTKFacts: Czech Datasets for Fact Verification},
-  journal   = {CoRR},
-  volume    = {abs/2201.11115},
-  year      = {2022},
-  url       = {https://arxiv.org/abs/2201.11115},
-  eprinttype = {arXiv},
-  eprint    = {2201.11115},
-  timestamp = {Tue, 01 Feb 2022 14:59:01 +0100},
-  biburl    = {https://dblp.org/rec/journals/corr/abs-2201-11115.bib},
-  bibsource = {dblp computer science bibliography, https://dblp.org}
-}
-
-```
+<!-- This model card has been generated automatically according to the information Keras had access to. You should
+probably proofread and complete it, then remove this comment. -->
+
+# xlm-roberta-large-xnli-csfever
+
+This model was trained from scratch on an unknown dataset.
+It achieves the following results on the evaluation set:
+
+
+## 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:
+- optimizer: None
+- training_precision: float32
+
+### Training results
+
+
+
+### Framework versions
 
+- Transformers 4.21.0
+- TensorFlow 2.7.1
+- Datasets 2.4.0
+- Tokenizers 0.12.1

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