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_single_dataset
+  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_single_dataset
+
+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: 0.1312
+- Precision: 0.6382
+- Recall: 0.6581
+- F1: 0.6480
+- Accuracy: 0.9631
+
+## 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 |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0925        | 1.0   | 3272  | 0.0913          | 0.6363    | 0.6521 | 0.6441 | 0.9624   |
+| 0.0707        | 2.0   | 6544  | 0.0937          | 0.6491    | 0.6611 | 0.6550 | 0.9637   |
+| 0.0607        | 3.0   | 9816  | 0.1028          | 0.6480    | 0.6591 | 0.6535 | 0.9626   |
+| 0.0522        | 4.0   | 13088 | 0.1076          | 0.6175    | 0.6910 | 0.6522 | 0.9610   |
+| 0.0485        | 5.0   | 16360 | 0.1087          | 0.6732    | 0.6208 | 0.6459 | 0.9640   |
+| 0.0472        | 6.0   | 19632 | 0.1140          | 0.6431    | 0.6334 | 0.6382 | 0.9622   |
+| 0.0454        | 7.0   | 22904 | 0.1232          | 0.6113    | 0.7110 | 0.6574 | 0.9609   |
+| 0.0431        | 8.0   | 26176 | 0.1285          | 0.6750    | 0.6237 | 0.6484 | 0.9636   |
+| 0.0427        | 9.0   | 29448 | 0.1301          | 0.6273    | 0.6609 | 0.6437 | 0.9610   |
+| 0.0409        | 10.0  | 32720 | 0.1312          | 0.6382    | 0.6581 | 0.6480 | 0.9631   |
+
+
+### Framework versions
+
+- Transformers 4.50.0
+- Pytorch 2.6.0+cu124
+- Datasets 3.4.1
+- Tokenizers 0.21.1

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