Model save

README.md

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+---
+license: cc-by-nc-sa-4.0
+base_model: ufal/robeczech-base
+tags:
+- generated_from_trainer
+datasets:
+- cnec
+metrics:
+- precision
+- recall
+- f1
+- accuracy
+model-index:
+- name: CNEC_1_1_robeczech-base
+  results:
+  - task:
+      name: Token Classification
+      type: token-classification
+    dataset:
+      name: cnec
+      type: cnec
+      config: default
+      split: validation
+      args: default
+    metrics:
+    - name: Precision
+      type: precision
+      value: 0.8354960234407702
+    - name: Recall
+      type: recall
+      value: 0.8812362030905078
+    - name: F1
+      type: f1
+      value: 0.8577567683712936
+    - name: Accuracy
+      type: accuracy
+      value: 0.9450064850843061
+---
+
+<!-- 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. -->
+
+# CNEC_1_1_robeczech-base
+
+This model is a fine-tuned version of [ufal/robeczech-base](https://huggingface.co/ufal/robeczech-base) on the cnec dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2816
+- Precision: 0.8355
+- Recall: 0.8812
+- F1: 0.8578
+- Accuracy: 0.9450
+
+## 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: 80
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Precision | Recall | F1     | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
+| 0.7852        | 10.2  | 1500  | 0.6287          | 0.3577    | 0.2375 | 0.2855 | 0.8413   |
+| 0.3806        | 20.41 | 3000  | 0.3455          | 0.7275    | 0.7779 | 0.7519 | 0.9240   |
+| 0.2384        | 30.61 | 4500  | 0.2764          | 0.8139    | 0.8552 | 0.8340 | 0.9383   |
+| 0.1722        | 40.82 | 6000  | 0.2640          | 0.8361    | 0.8693 | 0.8524 | 0.9450   |
+| 0.1357        | 51.02 | 7500  | 0.2666          | 0.8362    | 0.8702 | 0.8529 | 0.9454   |
+| 0.1115        | 61.22 | 9000  | 0.2697          | 0.8423    | 0.8751 | 0.8584 | 0.9457   |
+| 0.098         | 71.43 | 10500 | 0.2816          | 0.8355    | 0.8812 | 0.8578 | 0.9450   |
+
+
+### Framework versions
+
+- Transformers 4.36.2
+- Pytorch 2.1.2+cu121
+- Datasets 2.16.1
+- Tokenizers 0.15.0

model.safetensors

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