End of training

README.md

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+---
+license: apache-2.0
+base_model: google-bert/bert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: BERT_BIOMAT_NER3600_ST_DA
+  results: []
+---
+
+<!-- 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_BIOMAT_NER3600_ST_DA
+
+This model is a fine-tuned version of [google-bert/bert-base-uncased](https://huggingface.co/google-bert/bert-base-uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.3385
+- Precision: 0.9673
+- Recall: 0.9631
+- F1: 0.9652
+- Accuracy: 0.9636
+
+## 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: 32
+- eval_batch_size: 32
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.2217        | 1.0   | 601  | 0.2356          | 0.9543    | 0.9508 | 0.9525 | 0.9472   |
+| 0.0692        | 2.0   | 1202 | 0.2555          | 0.9571    | 0.9529 | 0.9550 | 0.9525   |
+| 0.0406        | 3.0   | 1803 | 0.2416          | 0.9626    | 0.9584 | 0.9605 | 0.9584   |
+| 0.0257        | 4.0   | 2404 | 0.2984          | 0.9644    | 0.9594 | 0.9619 | 0.9598   |
+| 0.011         | 5.0   | 3005 | 0.2851          | 0.9663    | 0.9622 | 0.9643 | 0.9627   |
+| 0.0079        | 6.0   | 3606 | 0.3022          | 0.9665    | 0.9622 | 0.9644 | 0.9627   |
+| 0.0056        | 7.0   | 4207 | 0.3214          | 0.9668    | 0.9619 | 0.9644 | 0.9625   |
+| 0.0043        | 8.0   | 4808 | 0.3227          | 0.9673    | 0.9631 | 0.9652 | 0.9636   |
+| 0.0036        | 9.0   | 5409 | 0.3405          | 0.9672    | 0.9629 | 0.9650 | 0.9634   |
+| 0.0025        | 10.0  | 6010 | 0.3385          | 0.9673    | 0.9631 | 0.9652 | 0.9636   |
+
+
+### Framework versions
+
+- Transformers 4.42.4
+- Pytorch 2.4.0+cu121
+- Datasets 2.21.0
+- Tokenizers 0.19.1

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