End of training

README.md

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+---
+library_name: transformers
+license: mit
+base_model: m3rg-iitd/matscibert
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: Final_Biomaterials_ST_cems_6000
+  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. -->
+
+# Final_Biomaterials_ST_cems_6000
+
+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: 0.0758
+- Precision: 0.9889
+- Recall: 0.9876
+- F1: 0.9883
+- Accuracy: 0.9887
+
+## 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: Use OptimizerNames.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 |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0304        | 1.0   | 1564  | 0.0325          | 0.9898    | 0.9862 | 0.9880 | 0.9886   |
+| 0.0203        | 2.0   | 3128  | 0.0347          | 0.9894    | 0.9886 | 0.9890 | 0.9893   |
+| 0.0114        | 3.0   | 4692  | 0.0397          | 0.9882    | 0.9886 | 0.9884 | 0.9888   |
+| 0.0063        | 4.0   | 6256  | 0.0496          | 0.9887    | 0.9878 | 0.9883 | 0.9885   |
+| 0.0048        | 5.0   | 7820  | 0.0550          | 0.9892    | 0.9876 | 0.9884 | 0.9887   |
+| 0.0028        | 6.0   | 9384  | 0.0609          | 0.9886    | 0.9875 | 0.9880 | 0.9884   |
+| 0.0021        | 7.0   | 10948 | 0.0658          | 0.9893    | 0.9869 | 0.9881 | 0.9886   |
+| 0.0012        | 8.0   | 12512 | 0.0724          | 0.9886    | 0.9884 | 0.9885 | 0.9888   |
+| 0.0012        | 9.0   | 14076 | 0.0737          | 0.9890    | 0.9878 | 0.9884 | 0.9888   |
+| 0.0007        | 10.0  | 15640 | 0.0758          | 0.9889    | 0.9876 | 0.9883 | 0.9887   |
+
+
+### Framework versions
+
+- Transformers 4.48.3
+- Pytorch 2.5.1+cu124
+- Datasets 3.3.1
+- Tokenizers 0.21.0

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runs/Feb17_23-04-35_850230746a8b/events.out.tfevents.1739833480.850230746a8b.4045.0

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