End of training

README.md

@@ -0,0 +1,100 @@
+---
+library_name: transformers
+license: apache-2.0
+base_model: google-bert/bert-base-uncased
+tags:
+- generated_from_trainer
+datasets:
+- biobert_json
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bert-base-uncased-finetuned-ner
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: biobert_json
+      type: biobert_json
+      config: Biobert_json
+      split: validation
+      args: Biobert_json
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.9437070282658518
+    - name: Recall
+      type: recall
+      value: 0.9691575953711876
+    - name: F1
+      type: f1
+      value: 0.9562630025642267
+    - name: Accuracy
+      type: accuracy
+      value: 0.977555086732302
+---
+
+<!-- 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. -->
+
+# bert-base-uncased-finetuned-ner
+
+This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on the biobert_json dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1107
+- Precision: 0.9437
+- Recall: 0.9692
+- F1: 0.9563
+- Accuracy: 0.9776
+
+## Model description
+
+More information needed
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.4381        | 1.0   | 612  | 0.1172          | 0.9235    | 0.9536 | 0.9383 | 0.9689   |
+| 0.1389        | 2.0   | 1224 | 0.1117          | 0.9247    | 0.9731 | 0.9483 | 0.9717   |
+| 0.0935        | 3.0   | 1836 | 0.0962          | 0.9433    | 0.9662 | 0.9546 | 0.9769   |
+| 0.0758        | 4.0   | 2448 | 0.0926          | 0.9408    | 0.9736 | 0.9569 | 0.9771   |
+| 0.0536        | 5.0   | 3060 | 0.0958          | 0.9404    | 0.9722 | 0.9561 | 0.9769   |
+| 0.0476        | 6.0   | 3672 | 0.1029          | 0.9418    | 0.9681 | 0.9548 | 0.9761   |
+| 0.0395        | 7.0   | 4284 | 0.1023          | 0.9425    | 0.9720 | 0.9570 | 0.9769   |
+| 0.0375        | 8.0   | 4896 | 0.1091          | 0.9426    | 0.9695 | 0.9559 | 0.9771   |
+| 0.0299        | 9.0   | 5508 | 0.1080          | 0.9451    | 0.9693 | 0.9570 | 0.9778   |
+| 0.0266        | 10.0  | 6120 | 0.1107          | 0.9437    | 0.9692 | 0.9563 | 0.9776   |
+
+
+### Framework versions
+
+- Transformers 4.46.3
+- Pytorch 2.5.1+cu121
+- Datasets 3.1.0
+- Tokenizers 0.20.3

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:07c9f6479696b14c8bc9f83618d2de5d5e0717e7b352abdc401313076f7b6fa4
+oid sha256:817c67a3d090e4a7e948e9d742b3d3fab58d4ccc45dd8bcc16220429512e5dbc
 size 435682216

runs/Dec05_17-47-39_b4a005ede56c/events.out.tfevents.1733420870.b4a005ede56c.1626.0

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:b65551373c495a523d34a669dc1a6dab347f6f4e90aee3888fee095c690eb427
-size 13145
+oid sha256:581efe029a9a301b0af027fc330cb40ac0aa65490253edb568908ee531709809
+size 13971

runs/Dec05_17-47-39_b4a005ede56c/events.out.tfevents.1733421435.b4a005ede56c.1626.1

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:0dd3cab50bb0024f716914b00c426eb0e81cd255fea72ae37d36316192c02699
+size 560