End of training

README.md

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+---
+library_name: transformers
+language:
+- np
+license: apache-2.0
+base_model: google-bert/bert-base-multilingual-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: Nepali-BERT-sentiment
+  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. -->
+
+# Nepali-BERT-sentiment
+
+This model is a fine-tuned version of [google-bert/bert-base-multilingual-uncased](https://huggingface.co/google-bert/bert-base-multilingual-uncased) on the Custom Devangari Datasets dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6887
+- Accuracy: 0.8660
+- F1: 0.4658
+- Precision: 0.4343
+- Recall: 0.5021
+
+## 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
+- lr_scheduler_warmup_steps: 500
+- num_epochs: 5
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.5999        | 1.0   | 595  | 0.5313          | 0.7274   | 0.3965 | 0.2670    | 0.7700 |
+| 0.5114        | 2.0   | 1190 | 0.4717          | 0.7745   | 0.4427 | 0.3106    | 0.7700 |
+| 0.4005        | 3.0   | 1785 | 0.4986          | 0.7907   | 0.4556 | 0.3266    | 0.7532 |
+| 0.3087        | 4.0   | 2380 | 0.6887          | 0.8660   | 0.4658 | 0.4343    | 0.5021 |
+| 0.2292        | 5.0   | 2975 | 0.8148          | 0.8626   | 0.4615 | 0.4240    | 0.5063 |
+
+
+### Framework versions
+
+- Transformers 4.44.2
+- Pytorch 2.4.1+cu121
+- Datasets 3.0.2
+- Tokenizers 0.19.1

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