End of training

README.md

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+---
+library_name: transformers
+base_model: raulgdp/xml-roberta-large-finetuned-ner
+tags:
+- generated_from_trainer
+datasets:
+- biobert_json
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: NER-finetuning-XML-RoBERTa-BIOBERT
+  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: 0.937247539398077
+    - name: Recall
+      type: recall
+      value: 0.964689348246179
+    - name: F1
+      type: f1
+      value: 0.9507704738269752
+    - name: Accuracy
+      type: accuracy
+      value: 0.9773235561218265
+---
+
+<!-- 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-finetuning-XML-RoBERTa-BIOBERT
+
+This model is a fine-tuned version of [raulgdp/xml-roberta-large-finetuned-ner](https://huggingface.co/raulgdp/xml-roberta-large-finetuned-ner) on the biobert_json dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1065
+- Precision: 0.9372
+- Recall: 0.9647
+- F1: 0.9508
+- Accuracy: 0.9773
+
+## 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: 4
+- eval_batch_size: 4
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.1305        | 1.0   | 2447  | 0.1005          | 0.9298    | 0.9680 | 0.9485 | 0.9747   |
+| 0.0874        | 2.0   | 4894  | 0.0981          | 0.9406    | 0.9711 | 0.9556 | 0.9781   |
+| 0.0782        | 3.0   | 7341  | 0.1023          | 0.9245    | 0.9577 | 0.9408 | 0.9747   |
+| 0.0807        | 4.0   | 9788  | 0.1042          | 0.9316    | 0.9567 | 0.9440 | 0.9753   |
+| 0.0437        | 5.0   | 12235 | 0.1065          | 0.9372    | 0.9647 | 0.9508 | 0.9773   |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.5.0+cu121
+- Datasets 3.1.0
+- Tokenizers 0.19.1