End of training

README.md

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+---
+license: mit
+base_model: m3rg-iitd/matscibert
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: MatSciBERT_BIOMAT_NER1800
+  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. -->
+
+# MatSciBERT_BIOMAT_NER1800
+
+This model is a fine-tuned version of [m3rg-iitd/matscibert](https://huggingface.co/m3rg-iitd/matscibert) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1788
+- Precision: 0.9841
+- Recall: 0.9758
+- F1: 0.9799
+- Accuracy: 0.9728
+
+## 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: 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 |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.186         | 1.0   | 869  | 0.0890          | 0.9831    | 0.9762 | 0.9796 | 0.9730   |
+| 0.0519        | 2.0   | 1738 | 0.0944          | 0.9834    | 0.9773 | 0.9803 | 0.9744   |
+| 0.0293        | 3.0   | 2607 | 0.1101          | 0.9832    | 0.9748 | 0.9790 | 0.9721   |
+| 0.0185        | 4.0   | 3476 | 0.1348          | 0.9823    | 0.9752 | 0.9788 | 0.9721   |
+| 0.0086        | 5.0   | 4345 | 0.1421          | 0.9823    | 0.9746 | 0.9785 | 0.9715   |
+| 0.0054        | 6.0   | 5214 | 0.1755          | 0.9835    | 0.9719 | 0.9777 | 0.9693   |
+| 0.0032        | 7.0   | 6083 | 0.1706          | 0.9831    | 0.9735 | 0.9783 | 0.9709   |
+| 0.0027        | 8.0   | 6952 | 0.1774          | 0.9840    | 0.9756 | 0.9798 | 0.9729   |
+| 0.0017        | 9.0   | 7821 | 0.1825          | 0.9841    | 0.9749 | 0.9795 | 0.9717   |
+| 0.001         | 10.0  | 8690 | 0.1788          | 0.9841    | 0.9758 | 0.9799 | 0.9728   |
+
+
+### Framework versions
+
+- Transformers 4.42.4
+- Pytorch 2.4.0+cu121
+- Datasets 2.21.0
+- Tokenizers 0.19.1

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runs/Sep01_15-00-06_fcb107e610d6/events.out.tfevents.1725202808.fcb107e610d6.8744.0

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