update model card README.md

README.md

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+---
+license: mit
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: BiBert-Classification
+  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. -->
+
+# BiBert-Classification
+
+This model is a fine-tuned version of [nlptown/bert-base-multilingual-uncased-sentiment](https://huggingface.co/nlptown/bert-base-multilingual-uncased-sentiment) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.0853
+- Accuracy: 0.7433
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 1.0981        | 1.0   | 9718  | 1.1034          | 0.7328   |
+| 1.0394        | 2.0   | 19436 | 1.0853          | 0.7433   |
+| 0.9649        | 3.0   | 29154 | 1.1041          | 0.7362   |
+| 0.8884        | 4.0   | 38872 | 1.1618          | 0.7315   |
+| 0.8005        | 5.0   | 48590 | 1.2340          | 0.7251   |
+
+
+### Framework versions
+
+- Transformers 4.21.1
+- Pytorch 1.12.1+cu113
+- Datasets 2.4.0
+- Tokenizers 0.12.1