End of training

README.md

@@ -0,0 +1,99 @@
+---
+license: apache-2.0
+base_model: distilbert-base-uncased
+tags:
+- generated_from_trainer
+datasets:
+- wnut_17
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: ner_model
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: wnut_17
+      type: wnut_17
+      config: wnut_17
+      split: test
+      args: wnut_17
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.5632040050062578
+    - name: Recall
+      type: recall
+      value: 0.4170528266913809
+    - name: F1
+      type: f1
+      value: 0.47923322683706066
+    - name: Accuracy
+      type: accuracy
+      value: 0.9478859390363815
+---
+
+<!-- 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. -->
+
+# ner_model
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the wnut_17 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3832
+- Precision: 0.5632
+- Recall: 0.4171
+- F1: 0.4792
+- Accuracy: 0.9479
+
+## 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: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 425  | 0.2828          | 0.6021    | 0.3800 | 0.4659 | 0.9466   |
+| 0.074         | 2.0   | 850  | 0.2955          | 0.5825    | 0.3892 | 0.4667 | 0.9474   |
+| 0.0457        | 3.0   | 1275 | 0.3072          | 0.5857    | 0.4180 | 0.4878 | 0.9492   |
+| 0.0234        | 4.0   | 1700 | 0.3430          | 0.5911    | 0.4059 | 0.4813 | 0.9481   |
+| 0.0144        | 5.0   | 2125 | 0.3468          | 0.5406    | 0.4198 | 0.4726 | 0.9476   |
+| 0.0107        | 6.0   | 2550 | 0.3742          | 0.5541    | 0.4032 | 0.4667 | 0.9470   |
+| 0.0107        | 7.0   | 2975 | 0.3779          | 0.5861    | 0.4133 | 0.4848 | 0.9483   |
+| 0.0081        | 8.0   | 3400 | 0.3802          | 0.5537    | 0.4013 | 0.4653 | 0.9477   |
+| 0.0059        | 9.0   | 3825 | 0.3750          | 0.5511    | 0.4198 | 0.4766 | 0.9478   |
+| 0.0033        | 10.0  | 4250 | 0.3832          | 0.5632    | 0.4171 | 0.4792 | 0.9479   |
+
+
+### Framework versions
+
+- Transformers 4.41.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.2
+- Tokenizers 0.19.1

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:3dcb48549d2fadd03f116654f7a89f0e0bab7502fda3e9a25e33b7a0cb151ec5
+oid sha256:8e65549fd9f90d1a5e9ae1b52c4a82b51bd9de9f276459be4474fe065b553240
 size 265503852