test-ner

README.md

@@ -1,7 +1,13 @@
 ---
 license: apache-2.0
+base_model: bert-base-uncased
 tags:
 - generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
 model-index:
 - name: test-ner
   results: []
@@ -13,6 +19,12 @@ should probably proofread and complete it, then remove this comment. -->
 # test-ner
 
 This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0693
+- Precision: 0.3093
+- Recall: 0.2664
+- F1: 0.2863
+- Accuracy: 0.9788
 
 ## Model description
 
@@ -37,18 +49,19 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
-- num_epochs: 1
+- num_epochs: 2
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| No log        | 1.0   | 80   | 0.0448          | 0.7933    | 0.7972 | 0.7952 | 0.9939   |
+| 0.1576        | 1.0   | 78   | 0.0892          | 0.1865    | 0.1264 | 0.1507 | 0.9736   |
+| 0.039         | 2.0   | 156  | 0.0693          | 0.3093    | 0.2664 | 0.2863 | 0.9788   |
 
 
 ### Framework versions
 
-- Transformers 4.27.4
-- Pytorch 2.3.1
-- Datasets 2.19.2
-- Tokenizers 0.13.3
+- Transformers 4.36.2
+- Pytorch 2.2.2
+- Datasets 2.19.1
+- Tokenizers 0.15.2

config.json

@@ -31,7 +31,7 @@
   "pad_token_id": 0,
   "position_embedding_type": "absolute",
   "torch_dtype": "float32",
-  "transformers_version": "4.27.4",
+  "transformers_version": "4.36.2",
   "type_vocab_size": 2,
   "use_cache": true,
   "vocab_size": 30522

model.safetensors

@@ -0,0 +1,3 @@
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+size 435602240

tokenizer_config.json

@@ -1,11 +1,53 @@
 {
+  "added_tokens_decoder": {
+    "0": {
+      "content": "[PAD]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "100": {
+      "content": "[UNK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "101": {
+      "content": "[CLS]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "102": {
+      "content": "[SEP]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "103": {
+      "content": "[MASK]",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "clean_up_tokenization_spaces": true,
   "cls_token": "[CLS]",
   "do_lower_case": true,
   "mask_token": "[MASK]",
   "model_max_length": 512,
   "pad_token": "[PAD]",
   "sep_token": "[SEP]",
-  "special_tokens_map_file": null,
   "strip_accents": null,
   "tokenize_chinese_chars": true,
   "tokenizer_class": "BertTokenizer",

training_args.bin

@@ -1,3 +1,3 @@
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-size 4024
+oid sha256:4ac092c31f304d6e91c86d7daff73b6b70e2a2fad0734a22cdbf2dea4e8ffb42
+size 4664