Update README.md

README.md

@@ -1,3 +1,81 @@
 ---
+datasets:
+- glue
+model-index:
+- name: contriever-mnli
+  results: []
+pipeline_tag: zero-shot-classification
+language:
+- en
 license: mit
 ---
+
+# contriever-mnli
+
+This model is a fine-tuned version of [facebook/contriever](https://huggingface.co/facebook/contriever) on the glue dataset.
+
+## Model description
+
+[Unsupervised Dense Information Retrieval with Contrastive Learning](https://arxiv.org/abs/2112.09118).
+Gautier Izacard, Mathilde Caron, Lucas Hosseini, Sebastian Riedel, Piotr Bojanowski, Armand Joulin, Edouard Grave, arXiv 2021
+
+## How to use the model
+
+The model can be loaded with the `zero-shot-classification` pipeline like so:
+
+```python
+from transformers import pipeline
+classifier = pipeline("zero-shot-classification",
+                      model="mjwong/contriever-mnli")
+```
+
+You can then use this pipeline to classify sequences into any of the class names you specify.
+
+```python
+sequence_to_classify = "one day I will see the world"
+candidate_labels = ['travel', 'cooking', 'dancing']
+classifier(sequence_to_classify, candidate_labels)
+#{'sequence': 'one day I will see the world',
+# 'labels': ['travel', 'cooking', 'dancing'],
+# 'scores': [0.7728410363197327, 0.13207288086414337, 0.09508601576089859]}
+```
+
+If more than one candidate label can be correct, pass `multi_class=True` to calculate each class independently:
+
+```python
+candidate_labels = ['travel', 'cooking', 'dancing', 'exploration']
+classifier(sequence_to_classify, candidate_labels, multi_class=True)
+#{'sequence': 'one day I will see the world',
+# 'labels': ['exploration', 'travel', 'cooking', 'dancing'],
+# 'scores': [0.9920766353607178,
+#  0.7247188091278076,
+#  0.08411424607038498,
+3  0.03875880688428879]}
+```
+
+### Eval results
+The model was evaluated using the dev sets for MultiNLI and test sets for ANLI. The metric used is accuracy.
+
+|Datasets|mnli_dev_m|mnli_dev_mm|anli_test_r1|anli_test_r2|anli_test_r3|
+| :---: | :---: | :---: | :---: | :---: | :---: |
+|[contriever-mnli](https://huggingface.co/mjwong/contriever-mnli)|0.821|0.822|0.247|0.281|0.312|
+|[contriever-msmarco-mnli](https://huggingface.co/mjwong/contriever-msmarco-mnli)|0.820|0.819|0.244|0.296|0.306|
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+
+- learning_rate: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 5
+
+### Framework versions
+- Transformers 4.28.1
+- Pytorch 1.12.1+cu116
+- Datasets 2.11.0
+- Tokenizers 0.12.1