Model save

README.md

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+---
+license: mit
+base_model: nlptown/bert-base-multilingual-uncased-sentiment
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: test_bert
+  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. -->
+
+# test_bert
+
+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: 0.8332
+- Accuracy: 0.6817
+
+## 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: 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: 2
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.1121        | 0.13  | 500  | 0.9841          | 0.6302   |
+| 1.0067        | 0.25  | 1000 | 0.9490          | 0.6499   |
+| 0.9325        | 0.38  | 1500 | 0.9200          | 0.6577   |
+| 0.9301        | 0.51  | 2000 | 0.9684          | 0.6418   |
+| 0.927         | 0.63  | 2500 | 0.9837          | 0.6234   |
+| 0.9067        | 0.76  | 3000 | 0.8973          | 0.6572   |
+| 0.8986        | 0.88  | 3500 | 0.8663          | 0.6747   |
+| 0.8964        | 1.01  | 4000 | 0.8408          | 0.6767   |
+| 0.8115        | 1.14  | 4500 | 0.8478          | 0.6696   |
+| 0.8081        | 1.26  | 5000 | 0.8600          | 0.6681   |
+| 0.7896        | 1.39  | 5500 | 0.8569          | 0.6747   |
+| 0.8075        | 1.52  | 6000 | 0.8353          | 0.6767   |
+| 0.802         | 1.64  | 6500 | 0.8261          | 0.6767   |
+| 0.768         | 1.77  | 7000 | 0.8289          | 0.6782   |
+| 0.7505        | 1.9   | 7500 | 0.8332          | 0.6817   |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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