Best span identification adapter from 5-fold CV (F1: 0.5869)

adapter_config.json

@@ -0,0 +1,43 @@
+{
+  "config": {
+    "adapter_residual_before_ln": false,
+    "cross_adapter": false,
+    "dropout": 0.0,
+    "factorized_phm_W": true,
+    "factorized_phm_rule": false,
+    "hypercomplex_nonlinearity": "glorot-uniform",
+    "init_weights": "bert",
+    "init_weights_seed": null,
+    "inv_adapter": null,
+    "inv_adapter_reduction_factor": null,
+    "is_parallel": false,
+    "learn_phm": true,
+    "leave_out": [],
+    "ln_after": false,
+    "ln_before": false,
+    "mh_adapter": true,
+    "non_linearity": "gelu",
+    "original_ln_after": true,
+    "original_ln_before": true,
+    "output_adapter": true,
+    "phm_bias": true,
+    "phm_c_init": "normal",
+    "phm_dim": 4,
+    "phm_init_range": 0.0001,
+    "phm_layer": false,
+    "phm_rank": 1,
+    "reduction_factor": 16,
+    "residual_before_ln": true,
+    "scaling": 1.0,
+    "shared_W_phm": false,
+    "shared_phm_rule": true,
+    "stochastic_depth": 0.0,
+    "use_gating": false
+  },
+  "hidden_size": 768,
+  "model_class": "XLMRobertaAdapterModel",
+  "model_name": "xlm-roberta-base",
+  "model_type": "xlm-roberta",
+  "name": "span_adapter",
+  "version": "adapters.1.2.0"
+}

head_config.json

@@ -0,0 +1,19 @@
+{
+  "config": {
+    "activation_function": "tanh",
+    "dropout_prob": null,
+    "head_type": "tagging",
+    "label2id": {
+      "NON-SPAN": 0,
+      "SPAN": 1
+    },
+    "layers": 1,
+    "num_labels": 2
+  },
+  "hidden_size": 768,
+  "model_class": "XLMRobertaAdapterModel",
+  "model_name": "xlm-roberta-base",
+  "model_type": "xlm-roberta",
+  "name": "span_adapter",
+  "version": "adapters.1.2.0"
+}

pytorch_adapter.bin

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+size 7192563

pytorch_model_head.bin

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+size 8125