init

config.json

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+{
+  "_name_or_path": "xlm-roberta-base",
+  "architectures": [
+    "XLMRobertaForTokenClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "eos_token_id": 2,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "B-dna",
+    "1": "I-dna",
+    "2": "O",
+    "3": "B-protein",
+    "4": "I-protein",
+    "5": "B-cell type",
+    "6": "I-cell type",
+    "7": "B-cell line",
+    "8": "I-cell line",
+    "9": "B-rna",
+    "10": "I-rna"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "B-cell line": 7,
+    "B-cell type": 5,
+    "B-dna": 0,
+    "B-protein": 3,
+    "B-rna": 9,
+    "I-cell line": 8,
+    "I-cell type": 6,
+    "I-dna": 1,
+    "I-protein": 4,
+    "I-rna": 10,
+    "O": 2
+  },
+  "layer_norm_eps": 1e-05,
+  "max_position_embeddings": 514,
+  "model_type": "xlm-roberta",
+  "num_attention_heads": 12,
+  "num_hidden_layers": 12,
+  "output_past": true,
+  "pad_token_id": 1,
+  "type_vocab_size": 1,
+  "vocab_size": 250002
+}

parameter.json

@@ -0,0 +1 @@
+{"dataset": ["bionlp2004"], "transformers_model": "xlm-roberta-base", "random_seed": 1234, "lr": 1e-05, "total_step": 13000, "warmup_step": 700, "weight_decay": 1e-07, "batch_size": 16, "max_seq_length": 128, "fp16": false, "max_grad_norm": 1.0, "lower_case": true, "checkpoint_prefix": null}

pytorch_model.bin

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+version https://git-lfs.github.com/spec/v1
+oid sha256:250151ec98d46a86c5779d22b98a1297f8dfd16350117e11c45ce3819c3d1ff2
+size 1109931409

sentencepiece.bpe.model

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+version https://git-lfs.github.com/spec/v1
+oid sha256:cfc8146abe2a0488e9e2a0c56de7952f7c11ab059eca145a0a727afce0db2865
+size 5069051

special_tokens_map.json

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+{"bos_token": "<s>", "eos_token": "</s>", "unk_token": "<unk>", "sep_token": "</s>", "pad_token": "<pad>", "cls_token": "<s>", "mask_token": "<mask>"}

test_bc5cdr_span_lower.json

@@ -0,0 +1 @@
+{"valid": {"f1": 0.0, "recall": 0.0, "precision": 0.0, "summary": ""}, "test": {"f1": 0.0, "recall": 0.0, "precision": 0.0, "summary": ""}}

test_bionlp2004_lower.json

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+{"valid": {"f1": 73.35416442193731, "recall": 78.75983341045813, "precision": 68.6428715466828, "summary": "              precision    recall  f1-score   support\n\n   cell line       0.49      0.69      0.58       500\n   cell type       0.77      0.72      0.74      1920\n         dna       0.64      0.74      0.69      1054\n     protein       0.69      0.83      0.76      5052\n         rna       0.65      0.76      0.70       118\n\n   micro avg       0.69      0.79      0.73      8644\n   macro avg       0.65      0.75      0.69      8644\nweighted avg       0.69      0.79      0.73      8644\n"}}

test_bionlp2004_span_lower.json

@@ -0,0 +1 @@
+{"valid": {"f1": 78.65655471289274, "recall": 83.98889403054142, "precision": 73.96088019559902, "summary": "              precision    recall  f1-score   support\n\n      entity       0.74      0.84      0.79      8644\n\n   micro avg       0.74      0.84      0.79      8644\n   macro avg       0.74      0.84      0.79      8644\nweighted avg       0.74      0.84      0.79      8644\n"}}

test_conll2003_span_lower.json

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+{"valid": {"f1": 0.0, "recall": 0.0, "precision": 0.0, "summary": ""}, "test": {"f1": 0.0, "recall": 0.0, "precision": 0.0, "summary": ""}}

test_fin_span_lower.json

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+{"valid": {"f1": 0.0, "recall": 0.0, "precision": 0.0, "summary": ""}}

test_mit_movie_trivia_span_lower.json

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+{"valid": {"f1": 0.0, "recall": 0.0, "precision": 0.0, "summary": ""}}

test_mit_restaurant_span_lower.json

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+{"valid": {"f1": 0.0, "recall": 0.0, "precision": 0.0, "summary": ""}}

test_ontonotes5_span_lower.json

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+{"valid": {"f1": 0.0, "recall": 0.0, "precision": 0.0, "summary": ""}, "test": {"f1": 0.0, "recall": 0.0, "precision": 0.0, "summary": ""}}

test_panx_dataset-en_span_lower.json

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+{"valid": {"f1": 0.0, "recall": 0.0, "precision": 0.0, "summary": ""}, "test": {"f1": 0.0, "recall": 0.0, "precision": 0.0, "summary": ""}}

test_wnut2017_span_lower.json

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+{"valid": {"f1": 0.0, "recall": 0.0, "precision": 0.0, "summary": ""}, "test": {"f1": 0.0, "recall": 0.0, "precision": 0.0, "summary": ""}}

tokenizer_config.json

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+{"bos_token": "<s>", "eos_token": "</s>", "sep_token": "</s>", "cls_token": "<s>", "unk_token": "<unk>", "pad_token": "<pad>", "mask_token": "<mask>", "model_max_length": 512, "name_or_path": "xlm-roberta-base"}