Initial version.

README.md

@@ -0,0 +1,53 @@
+---
+tags:
+- roberta
+- adapterhub:dp/ud_ewt
+- adapter-transformers
+datasets:
+- universal_dependencies
+language:
+- en
+---
+
+# Adapter `AdapterHub/roberta-base-pf-ud_en_ewt` for roberta-base
+
+An [adapter](https://adapterhub.ml) for the `roberta-base` model that was trained on the [dp/ud_ewt](https://adapterhub.ml/explore/dp/ud_ewt/) dataset and includes a prediction head for dependency parsing.
+
+This adapter was created for usage with the **[adapter-transformers](https://github.com/Adapter-Hub/adapter-transformers)** library.
+
+## Usage
+
+First, install `adapter-transformers`:
+
+```
+pip install -U adapter-transformers
+```
+_Note: adapter-transformers is a fork of transformers that acts as a drop-in replacement with adapter support. [More](https://docs.adapterhub.ml/installation.html)_
+
+Now, the adapter can be loaded and activated like this:
+
+```python
+from transformers import AutoModelWithHeads
+
+model = AutoModelWithHeads.from_pretrained("roberta-base")
+adapter_name = model.load_adapter("AdapterHub/roberta-base-pf-ud_en_ewt", source="hf", set_active=True)
+```
+
+## Architecture & Training
+
+This adapter was trained using adapter-transformer's example script for dependency parsing.
+See https://github.com/Adapter-Hub/adapter-transformers/tree/master/examples/dependency-parsing.
+
+
+## Evaluation results
+
+Scores achieved by dependency parsing adapters on the test set of UD English EWT after training:
+| | UAS | LAS |
+| --- | --- | --- |
+| `bert-base-uncased` | 91.74 | 89.15 |
+| `roberta-base` | 91.43 | 88.43 |
+
+
+## Citation
+
+<!-- Add some description here -->

adapter_config.json

@@ -0,0 +1,23 @@
+{
+  "config": {
+    "adapter_residual_before_ln": false,
+    "cross_adapter": false,
+    "inv_adapter": null,
+    "inv_adapter_reduction_factor": null,
+    "leave_out": [],
+    "ln_after": false,
+    "ln_before": false,
+    "mh_adapter": false,
+    "non_linearity": "relu",
+    "original_ln_after": true,
+    "original_ln_before": true,
+    "output_adapter": true,
+    "reduction_factor": 16,
+    "residual_before_ln": true
+  },
+  "hidden_size": 768,
+  "model_class": "RobertaModelWithHeads",
+  "model_name": "roberta-base",
+  "model_type": "roberta",
+  "name": "ud_en_ewt"
+}

head_config.json

@@ -0,0 +1,51 @@
+{
+  "config": {
+    "head_type": "dependency_parsing",
+    "label2id": {
+      "_": 0,
+      "acl": 1,
+      "advcl": 2,
+      "advmod": 3,
+      "amod": 4,
+      "appos": 5,
+      "aux": 6,
+      "case": 7,
+      "cc": 8,
+      "ccomp": 9,
+      "clf": 10,
+      "compound": 11,
+      "conj": 12,
+      "cop": 13,
+      "csubj": 14,
+      "dep": 15,
+      "det": 16,
+      "discourse": 17,
+      "dislocated": 18,
+      "expl": 19,
+      "fixed": 20,
+      "flat": 21,
+      "goeswith": 22,
+      "iobj": 23,
+      "list": 24,
+      "mark": 25,
+      "nmod": 26,
+      "nsubj": 27,
+      "nummod": 28,
+      "obj": 29,
+      "obl": 30,
+      "orphan": 31,
+      "parataxis": 32,
+      "punct": 33,
+      "reparandum": 34,
+      "root": 35,
+      "vocative": 36,
+      "xcomp": 37
+    },
+    "num_labels": 38
+  },
+  "hidden_size": 768,
+  "model_class": "RobertaModelWithHeads",
+  "model_name": "roberta-base",
+  "model_type": "roberta",
+  "name": "ud_en_ewt"
+}

pytorch_adapter.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:4228e30acd819a9fcbf48d56d167a49fe8b679e93455bf2a3224c5a0b67a1596
+size 3595375

pytorch_model_head.bin

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:b2e7919985e77aad5cb7e93b4d1c717f07373695f3592e5f895f01be64edac0d
+size 92250367