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_mnli
+  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_mnli
+
+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: 0.8077
+- Accuracy: 0.7532
+
+## 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 |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 0.7793        | 1.0   | 1534  | 0.6779          | 0.7105   |
+| 0.6313        | 2.0   | 3068  | 0.6316          | 0.7361   |
+| 0.5474        | 3.0   | 4602  | 0.6253          | 0.7505   |
+| 0.4766        | 4.0   | 6136  | 0.6401          | 0.7538   |
+| 0.414         | 5.0   | 7670  | 0.6470          | 0.7560   |
+| 0.3555        | 6.0   | 9204  | 0.7034          | 0.7555   |
+| 0.304         | 7.0   | 10738 | 0.7440          | 0.7554   |
+| 0.2609        | 8.0   | 12272 | 0.8077          | 0.7532   |
+
+
+### Framework versions
+
+- Transformers 4.46.3
+- Pytorch 2.2.1+cu118
+- Datasets 2.17.0
+- Tokenizers 0.20.3

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