Model save

README.md

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+---
+library_name: transformers
+base_model: gokulsrinivasagan/bert_base_lda_50_v1
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: bert_base_lda_50_v1_mrpc
+  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. -->
+
+# bert_base_lda_50_v1_mrpc
+
+This model is a fine-tuned version of [gokulsrinivasagan/bert_base_lda_50_v1](https://huggingface.co/gokulsrinivasagan/bert_base_lda_50_v1) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6254
+- Accuracy: 0.6838
+- F1: 0.8122
+- Combined Score: 0.7480
+
+## 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: 0.001
+- train_batch_size: 256
+- eval_batch_size: 256
+- seed: 10
+- optimizer: Use 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: 50
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Combined Score |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:--------------:|
+| 1.9018        | 1.0   | 15   | 1.7469          | 0.3162   | 0.0    | 0.1581         |
+| 0.7758        | 2.0   | 30   | 0.7136          | 0.6838   | 0.8122 | 0.7480         |
+| 0.6464        | 3.0   | 45   | 0.6402          | 0.6838   | 0.8122 | 0.7480         |
+| 0.6412        | 4.0   | 60   | 0.6261          | 0.6838   | 0.8122 | 0.7480         |
+| 0.6318        | 5.0   | 75   | 0.6251          | 0.6838   | 0.8122 | 0.7480         |
+| 0.6352        | 6.0   | 90   | 0.6246          | 0.6838   | 0.8122 | 0.7480         |
+| 0.635         | 7.0   | 105  | 0.6256          | 0.6838   | 0.8122 | 0.7480         |
+| 0.634         | 8.0   | 120  | 0.6244          | 0.6838   | 0.8122 | 0.7480         |
+| 0.6297        | 9.0   | 135  | 0.6349          | 0.6838   | 0.8122 | 0.7480         |
+| 0.6357        | 10.0  | 150  | 0.6226          | 0.6838   | 0.8122 | 0.7480         |
+| 0.6341        | 11.0  | 165  | 0.6256          | 0.6838   | 0.8122 | 0.7480         |
+| 0.6333        | 12.0  | 180  | 0.6250          | 0.6838   | 0.8122 | 0.7480         |
+| 0.6309        | 13.0  | 195  | 0.6240          | 0.6838   | 0.8122 | 0.7480         |
+| 0.6343        | 14.0  | 210  | 0.6259          | 0.6838   | 0.8122 | 0.7480         |
+| 0.6328        | 15.0  | 225  | 0.6254          | 0.6838   | 0.8122 | 0.7480         |
+
+
+### Framework versions
+
+- Transformers 4.46.3
+- Pytorch 2.2.1+cu118
+- Datasets 2.17.0
+- Tokenizers 0.20.3

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