Training complete

README.md

@@ -0,0 +1,92 @@
+---
+license: apache-2.0
+base_model: bert-base-cased
+tags:
+- generated_from_trainer
+datasets:
+- linnaeus
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: bert-linnaeus-ner
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: linnaeus
+      type: linnaeus
+      config: linnaeus
+      split: validation
+      args: linnaeus
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.9223433242506812
+    - name: Recall
+      type: recall
+      value: 0.9521800281293952
+    - name: F1
+      type: f1
+      value: 0.9370242214532872
+    - name: Accuracy
+      type: accuracy
+      value: 0.9985110458648063
+---
+
+<!-- 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-linnaeus-ner
+
+This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the linnaeus dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0073
+- Precision: 0.9223
+- Recall: 0.9522
+- F1: 0.9370
+- Accuracy: 0.9985
+
+## 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: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0076        | 1.0   | 1492 | 0.0128          | 0.8566    | 0.9578 | 0.9044 | 0.9967   |
+| 0.0024        | 2.0   | 2984 | 0.0082          | 0.9092    | 0.9578 | 0.9329 | 0.9980   |
+| 0.0007        | 3.0   | 4476 | 0.0073          | 0.9223    | 0.9522 | 0.9370 | 0.9985   |
+
+
+### Framework versions
+
+- Transformers 4.34.0
+- Pytorch 2.1.0+cu121
+- Datasets 2.14.5
+- Tokenizers 0.14.0