Training finish!

README.md

@@ -3,6 +3,8 @@ license: apache-2.0
 base_model: bert-base-cased
 tags:
 - generated_from_trainer
+datasets:
+- conll2003
 metrics:
 - precision
 - recall
@@ -10,7 +12,29 @@ metrics:
 - accuracy
 model-index:
 - name: bert-finetuned-ner
-  results: []
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: conll2003
+      type: conll2003
+      config: conll2003
+      split: validation
+      args: conll2003
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.9125862635557016
+    - name: Recall
+      type: recall
+      value: 0.9347021204981488
+    - name: F1
+      type: f1
+      value: 0.9235118057864983
+    - name: Accuracy
+      type: accuracy
+      value: 0.9822658503561547
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -18,13 +42,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # bert-finetuned-ner
 
-This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on an unknown dataset.
+This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the conll2003 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0719
-- Precision: 0.8805
-- Recall: 0.9236
-- F1: 0.9015
-- Accuracy: 0.9807
+- Loss: 0.0660
+- Precision: 0.9126
+- Recall: 0.9347
+- F1: 0.9235
+- Accuracy: 0.9823
 
 ## Model description
 
@@ -44,8 +68,8 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 2e-05
-- train_batch_size: 16
-- eval_batch_size: 16
+- train_batch_size: 8
+- eval_batch_size: 8
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
@@ -55,12 +79,12 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.2227        | 1.0   | 878  | 0.0719          | 0.8805    | 0.9236 | 0.9015 | 0.9807   |
+| 0.0756        | 1.0   | 1756 | 0.0660          | 0.9126    | 0.9347 | 0.9235 | 0.9823   |
 
 
 ### Framework versions
 
-- Transformers 4.36.2
-- Pytorch 2.1.2+cu121
+- Transformers 4.35.2
+- Pytorch 2.1.0
 - Datasets 2.16.1
 - Tokenizers 0.15.0

config.json

@@ -41,7 +41,7 @@
   "pad_token_id": 0,
   "position_embedding_type": "absolute",
   "torch_dtype": "float32",
-  "transformers_version": "4.36.2",
+  "transformers_version": "4.35.2",
   "type_vocab_size": 2,
   "use_cache": true,
   "vocab_size": 28996

model.safetensors

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 size 430929740

runs/Jan19_15-02-42_maxdeMac-mini.local/events.out.tfevents.1705647792.maxdeMac-mini.local.17782.0

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training_args.bin

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