End of training

README.md

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+---
+license: apache-2.0
+base_model: bert-base-multilingual-uncased
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: multibert2809_flow
+  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. -->
+
+# multibert2809_flow
+
+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: 0.4534
+- Precision: 0.7055
+- Recall: 0.7076
+- F1: 0.7066
+- Accuracy: 0.8709
+
+## 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: 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: 8
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| No log        | 1.0   | 118  | 0.5021          | 0.6550    | 0.6229 | 0.6385 | 0.8414   |
+| No log        | 2.0   | 236  | 0.4534          | 0.7055    | 0.7076 | 0.7066 | 0.8709   |
+| No log        | 3.0   | 354  | 0.4903          | 0.7455    | 0.7237 | 0.7345 | 0.8752   |
+| No log        | 4.0   | 472  | 0.5158          | 0.7488    | 0.7327 | 0.7407 | 0.8755   |
+| 0.3074        | 5.0   | 590  | 0.5685          | 0.7502    | 0.7434 | 0.7468 | 0.8758   |
+| 0.3074        | 6.0   | 708  | 0.5799          | 0.7612    | 0.7530 | 0.7570 | 0.8809   |
+| 0.3074        | 7.0   | 826  | 0.6022          | 0.7673    | 0.7494 | 0.7582 | 0.8791   |
+| 0.3074        | 8.0   | 944  | 0.6054          | 0.7663    | 0.7554 | 0.7608 | 0.8840   |
+
+
+### Framework versions
+
+- Transformers 4.33.2
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.13.3

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