Training complete

README.md

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+---
+base_model: DeepPavlov/rubert-base-cased
+tags:
+- generated_from_trainer
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: rubert-finetuned-ner
+  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. -->
+
+# rubert-finetuned-ner
+
+This model is a fine-tuned version of [DeepPavlov/rubert-base-cased](https://huggingface.co/DeepPavlov/rubert-base-cased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1536
+- Precision: 0.8904
+- Recall: 0.9077
+- F1: 0.8990
+- Accuracy: 0.9585
+
+## 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: 0.0001
+- train_batch_size: 16
+- eval_batch_size: 64
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.05
+- num_epochs: 2
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.0828        | 0.5   | 625  | 0.2171          | 0.8117    | 0.8616 | 0.8359 | 0.9391   |
+| 0.1195        | 1.0   | 1250 | 0.1753          | 0.8540    | 0.8842 | 0.8689 | 0.9488   |
+| 0.1255        | 1.5   | 1875 | 0.1754          | 0.8860    | 0.9027 | 0.8943 | 0.9577   |
+| 0.0546        | 2.0   | 2500 | 0.1536          | 0.8904    | 0.9077 | 0.8990 | 0.9585   |
+
+
+### Framework versions
+
+- Transformers 4.40.0
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.0
+- Tokenizers 0.19.1