End of training

README.md

@@ -1,5 +1,6 @@
 ---
 license: apache-2.0
+base_model: distilbert-base-uncased
 tags:
 - generated_from_trainer
 metrics:
@@ -7,28 +8,27 @@ metrics:
 - recall
 - f1
 - accuracy
-base_model: distilbert-base-uncased
 model-index:
-- name: kg_model
+- name: knowledge-graph-nlp
   results: []
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 should probably proofread and complete it, then remove this comment. -->
 
-# kg_model
+# knowledge-graph-nlp
 
 This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.3039
-- Precision: 0.7629
-- Recall: 0.7025
-- F1: 0.7315
-- Accuracy: 0.8965
+- Loss: 0.2719
+- Precision: 0.8636
+- Recall: 0.8409
+- F1: 0.8521
+- Accuracy: 0.9291
 
 ## Model description
 
-Lite model to extract entities and relation between them, could be leveraged for Question Answering and Querying tasks.
+More information needed
 
 ## Intended uses & limitations
 
@@ -55,15 +55,15 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.3736        | 1.0   | 1063 | 0.3379          | 0.7542    | 0.6217 | 0.6816 | 0.8813   |
-| 0.3078        | 2.0   | 2126 | 0.3075          | 0.7728    | 0.6678 | 0.7164 | 0.8929   |
-| 0.267         | 3.0   | 3189 | 0.3017          | 0.7597    | 0.6999 | 0.7285 | 0.8954   |
-| 0.2455        | 4.0   | 4252 | 0.3039          | 0.7629    | 0.7025 | 0.7315 | 0.8965   |
+| 0.1915        | 1.0   | 855  | 0.2499          | 0.8465    | 0.8228 | 0.8345 | 0.9227   |
+| 0.1345        | 2.0   | 1710 | 0.2609          | 0.8528    | 0.8370 | 0.8448 | 0.9259   |
+| 0.1078        | 3.0   | 2565 | 0.2664          | 0.8558    | 0.8450 | 0.8504 | 0.9285   |
+| 0.0949        | 4.0   | 3420 | 0.2719          | 0.8636    | 0.8409 | 0.8521 | 0.9291   |
 
 
 ### Framework versions
 
-- Transformers 4.27.3
-- Pytorch 1.13.1+cu116
-- Datasets 2.10.1
-- Tokenizers 0.13.2
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.17.0
+- Tokenizers 0.15.1

model.safetensors

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 size 265476168

runs/Feb14_08-09-42_c87e355fe59e/events.out.tfevents.1707898194.c87e355fe59e.433.1

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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": {
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+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
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+      "normalized": false,
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+      "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": "DistilBertTokenizer",

training_args.bin

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