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: MatSciBERT_ST_DA_100
+  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_ST_DA_100
+
+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: 0.2043
+- Precision: 0.9627
+- Recall: 0.9693
+- F1: 0.9660
+- Accuracy: 0.9561
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 59   | 0.2685          | 0.9263    | 0.9420 | 0.9341 | 0.9213   |
+| No log        | 2.0   | 118  | 0.1935          | 0.9477    | 0.9573 | 0.9524 | 0.9429   |
+| No log        | 3.0   | 177  | 0.2043          | 0.9558    | 0.9669 | 0.9613 | 0.9506   |
+| No log        | 4.0   | 236  | 0.1769          | 0.9596    | 0.9701 | 0.9648 | 0.9554   |
+| No log        | 5.0   | 295  | 0.1789          | 0.9619    | 0.9686 | 0.9652 | 0.9561   |
+| No log        | 6.0   | 354  | 0.1916          | 0.9620    | 0.9683 | 0.9651 | 0.9557   |
+| No log        | 7.0   | 413  | 0.1955          | 0.9623    | 0.9685 | 0.9654 | 0.9559   |
+| No log        | 8.0   | 472  | 0.2002          | 0.9627    | 0.9713 | 0.9670 | 0.9575   |
+| 0.1044        | 9.0   | 531  | 0.2033          | 0.9632    | 0.9698 | 0.9665 | 0.9566   |
+| 0.1044        | 10.0  | 590  | 0.2043          | 0.9627    | 0.9693 | 0.9660 | 0.9561   |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.0+cu121
+- Datasets 2.21.0
+- Tokenizers 0.19.1

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