End of training

README.md

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+---
+library_name: transformers
+license: cc-by-4.0
+base_model: NazaGara/NER-fine-tuned-BETO
+tags:
+- generated_from_trainer
+datasets:
+- biobert_json
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: NER-finetuning-BETO-CM-V1
+  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: 0.949653802801782
+    - name: Recall
+      type: recall
+      value: 0.9613670941099761
+    - name: F1
+      type: f1
+      value: 0.9554745511003105
+    - name: Accuracy
+      type: accuracy
+      value: 0.976855614973262
+---
+
+<!-- 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-BETO-CM-V1
+
+This model is a fine-tuned version of [NazaGara/NER-fine-tuned-BETO](https://huggingface.co/NazaGara/NER-fine-tuned-BETO) on the biobert_json dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1236
+- Precision: 0.9497
+- Recall: 0.9614
+- F1: 0.9555
+- Accuracy: 0.9769
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.3411        | 1.0   | 612  | 0.1137          | 0.9437    | 0.9474 | 0.9456 | 0.9707   |
+| 0.1072        | 2.0   | 1224 | 0.1090          | 0.9304    | 0.9685 | 0.9491 | 0.9727   |
+| 0.0757        | 3.0   | 1836 | 0.1024          | 0.9450    | 0.9692 | 0.9569 | 0.9768   |
+| 0.0589        | 4.0   | 2448 | 0.1050          | 0.9492    | 0.9666 | 0.9578 | 0.9774   |
+| 0.0419        | 5.0   | 3060 | 0.1054          | 0.9498    | 0.9621 | 0.9559 | 0.9771   |
+| 0.0365        | 6.0   | 3672 | 0.1124          | 0.9460    | 0.9583 | 0.9521 | 0.9753   |
+| 0.0299        | 7.0   | 4284 | 0.1119          | 0.9495    | 0.9632 | 0.9563 | 0.9774   |
+| 0.0282        | 8.0   | 4896 | 0.1187          | 0.9482    | 0.9625 | 0.9553 | 0.9771   |
+| 0.0221        | 9.0   | 5508 | 0.1203          | 0.9496    | 0.9608 | 0.9551 | 0.9768   |
+| 0.0192        | 10.0  | 6120 | 0.1236          | 0.9497    | 0.9614 | 0.9555 | 0.9769   |
+
+
+### Framework versions
+
+- Transformers 4.46.2
+- Pytorch 2.5.1+cu121
+- Datasets 3.1.0
+- Tokenizers 0.20.3

runs/Nov19_02-32-47_07e61589da2f/events.out.tfevents.1731984160.07e61589da2f.1211.1

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