Model save

README.md

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+---
+library_name: transformers
+base_model: gokulsrinivasagan/bert_tiny_lda_5_v1_book
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: bert_tiny_lda_5_v1_book_qnli
+  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_tiny_lda_5_v1_book_qnli
+
+This model is a fine-tuned version of [gokulsrinivasagan/bert_tiny_lda_5_v1_book](https://huggingface.co/gokulsrinivasagan/bert_tiny_lda_5_v1_book) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6156
+- Accuracy: 0.8171
+
+## 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: 5e-05
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.5111        | 1.0   | 410  | 0.4212          | 0.8082   |
+| 0.4041        | 2.0   | 820  | 0.3891          | 0.8252   |
+| 0.3396        | 3.0   | 1230 | 0.3795          | 0.8329   |
+| 0.2836        | 4.0   | 1640 | 0.4442          | 0.8228   |
+| 0.2279        | 5.0   | 2050 | 0.4809          | 0.8155   |
+| 0.1855        | 6.0   | 2460 | 0.5276          | 0.8263   |
+| 0.1468        | 7.0   | 2870 | 0.5409          | 0.8234   |
+| 0.1206        | 8.0   | 3280 | 0.6156          | 0.8171   |
+
+
+### Framework versions
+
+- Transformers 4.46.3
+- Pytorch 2.2.1+cu118
+- Datasets 2.17.0
+- Tokenizers 0.20.3

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