Training complete

README.md

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+---
+license: apache-2.0
+base_model: bert-base-cased
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: assignment2_meher_test2
+  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. -->
+
+# assignment2_meher_test2
+
+This model is a fine-tuned version of [bert-base-cased](https://huggingface.co/bert-base-cased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5440
+- Precision: 0.2070
+- Recall: 0.2440
+- F1: 0.2240
+- Accuracy: 0.9244
+
+## 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: 8
+- eval_batch_size: 8
+- 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   | 347  | 0.2833          | 0.1672    | 0.1787 | 0.1728 | 0.9252   |
+| 0.2912        | 2.0   | 694  | 0.3104          | 0.1923    | 0.2062 | 0.1990 | 0.9262   |
+| 0.1166        | 3.0   | 1041 | 0.3258          | 0.1973    | 0.2474 | 0.2195 | 0.9235   |
+| 0.1166        | 4.0   | 1388 | 0.3608          | 0.1818    | 0.3024 | 0.2271 | 0.9131   |
+| 0.054         | 5.0   | 1735 | 0.4753          | 0.2093    | 0.2165 | 0.2128 | 0.9239   |
+| 0.0277        | 6.0   | 2082 | 0.4959          | 0.2181    | 0.2405 | 0.2288 | 0.9246   |
+| 0.0277        | 7.0   | 2429 | 0.5534          | 0.2331    | 0.1890 | 0.2087 | 0.9309   |
+| 0.0159        | 8.0   | 2776 | 0.5215          | 0.2281    | 0.2509 | 0.2390 | 0.9254   |
+| 0.0091        | 9.0   | 3123 | 0.5522          | 0.2244    | 0.2405 | 0.2322 | 0.9256   |
+| 0.0091        | 10.0  | 3470 | 0.5440          | 0.2070    | 0.2440 | 0.2240 | 0.9244   |
+
+
+### Framework versions
+
+- Transformers 4.34.1
+- Pytorch 2.1.0+cu118
+- Datasets 2.14.6
+- Tokenizers 0.14.1

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