Initial Commit

config.json

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+{
+  "_name_or_path": "Davlan/xlm-roberta-base-finetuned-swahili",
+  "architectures": [
+    "XLMRobertaForTokenClassification"
+  ],
+  "attention_probs_dropout_prob": 0.1,
+  "bos_token_id": 0,
+  "classifier_dropout": null,
+  "eos_token_id": 2,
+  "gradient_checkpointing": false,
+  "hidden_act": "gelu",
+  "hidden_dropout_prob": 0.1,
+  "hidden_size": 768,
+  "id2label": {
+    "0": "O",
+    "1": "B-DATE",
+    "2": "I-DATE",
+    "3": "B-PER",
+    "4": "I-PER",
+    "5": "B-ORG",
+    "6": "I-ORG",
+    "7": "B-LOC",
+    "8": "I-LOC"
+  },
+  "initializer_range": 0.02,
+  "intermediate_size": 3072,
+  "label2id": {
+    "B-DATE": 1,
+    "B-LOC": 7,
+    "B-ORG": 5,
+    "B-PER": 3,
+    "I-DATE": 2,
+    "I-LOC": 8,
+    "I-ORG": 6,
+    "I-PER": 4,
+    "O": 0
+  },
+  "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,
+  "position_embedding_type": "absolute",
+  "torch_dtype": "float32",
+  "transformers_version": "4.11.3",
+  "type_vocab_size": 1,
+  "use_cache": true,
+  "vocab_size": 250002
+}

eval_results.txt

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+f1 = 0.896838602329451
+loss = 0.15985548422772808
+precision = 0.8953488372093024
+recall = 0.8983333333333333
+report =               precision    recall  f1-score   support
+
+        DATE       0.76      0.75      0.76        91
+         LOC       0.90      0.91      0.90       172
+         ORG       0.95      0.91      0.93       169
+         PER       0.91      0.95      0.93       168
+
+   micro avg       0.90      0.90      0.90       600
+   macro avg       0.88      0.88      0.88       600
+weighted avg       0.90      0.90      0.90       600
+

pytorch_model.bin

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+oid sha256:6eb890390dfae53dceac5bb275501a0f5562ce502c15b64719844884379b2f72
+size 1109924593

sentencepiece.bpe.model

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+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": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normalized": false}}

test_results.txt

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+f1 = 0.8492693110647181
+loss = 0.23357212637886277
+precision = 0.8363486842105263
+recall = 0.8625954198473282
+report =               precision    recall  f1-score   support
+
+        DATE       0.69      0.72      0.70       145
+         LOC       0.84      0.91      0.88       338
+         ORG       0.90      0.89      0.89       351
+         PER       0.83      0.85      0.84       345
+
+   micro avg       0.84      0.86      0.85      1179
+   macro avg       0.82      0.84      0.83      1179
+weighted avg       0.84      0.86      0.85      1179
+

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": {"content": "<mask>", "single_word": false, "lstrip": true, "rstrip": false, "normalized": true, "__type": "AddedToken"}, "model_max_length": 512, "special_tokens_map_file": null, "name_or_path": "Davlan/xlm-roberta-base-finetuned-swahili", "sp_model_kwargs": {}, "tokenizer_class": "XLMRobertaTokenizer"}

training_args.bin

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+size 1583