Model save

README.md

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+---
+license: apache-2.0
+base_model: bert-base-multilingual-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: bert_product_classifier_final
+  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_product_classifier_final
+
+This model is a fine-tuned version of [bert-base-multilingual-uncased](https://huggingface.co/bert-base-multilingual-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2344
+- Accuracy: 0.9470
+- F1: 0.9466
+- Precision: 0.9467
+- Recall: 0.9470
+
+## 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
+- num_epochs: 4
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.85          | 1.0   | 960  | 0.2943          | 0.9090   | 0.9074 | 0.9091    | 0.9090 |
+| 0.2538        | 2.0   | 1920 | 0.2250          | 0.9332   | 0.9331 | 0.9331    | 0.9332 |
+| 0.1468        | 3.0   | 2880 | 0.2372          | 0.9384   | 0.9388 | 0.9396    | 0.9384 |
+| 0.0937        | 4.0   | 3840 | 0.2344          | 0.9470   | 0.9466 | 0.9467    | 0.9470 |
+
+
+### Framework versions
+
+- Transformers 4.32.0
+- Pytorch 2.0.1+cu117
+- Datasets 2.14.4
+- Tokenizers 0.13.3