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: VF_MatSciBERT_ST_1800
+  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. -->
+
+# VF_MatSciBERT_ST_1800
+
+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: 0.1571
+- Precision: 0.9763
+- Recall: 0.9819
+- F1: 0.9791
+- Accuracy: 0.9755
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.1492        | 1.0   | 569  | 0.0954          | 0.9709    | 0.9754 | 0.9732 | 0.9704   |
+| 0.0548        | 2.0   | 1138 | 0.0934          | 0.9726    | 0.9785 | 0.9756 | 0.9726   |
+| 0.0348        | 3.0   | 1707 | 0.1098          | 0.9749    | 0.9801 | 0.9775 | 0.9738   |
+| 0.0213        | 4.0   | 2276 | 0.1268          | 0.9739    | 0.9813 | 0.9776 | 0.9735   |
+| 0.0141        | 5.0   | 2845 | 0.1326          | 0.9748    | 0.9806 | 0.9777 | 0.9740   |
+| 0.0093        | 6.0   | 3414 | 0.1402          | 0.9750    | 0.9808 | 0.9779 | 0.9743   |
+| 0.0062        | 7.0   | 3983 | 0.1541          | 0.9741    | 0.9805 | 0.9773 | 0.9733   |
+| 0.0033        | 8.0   | 4552 | 0.1682          | 0.9741    | 0.9814 | 0.9777 | 0.9732   |
+| 0.0026        | 9.0   | 5121 | 0.1638          | 0.9749    | 0.9821 | 0.9785 | 0.9743   |
+| 0.0021        | 10.0  | 5690 | 0.1571          | 0.9763    | 0.9819 | 0.9791 | 0.9755   |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.0+cu121
+- Datasets 2.21.0
+- Tokenizers 0.19.1

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runs/Sep05_13-26-29_0cf716ad2f0b/events.out.tfevents.1725542792.0cf716ad2f0b.162.0

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