End of training

README.md

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+---
+license: mit
+base_model: xlnet-base-cased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+- precision
+- recall
+model-index:
+- name: xlnet-base-cased-HU-comple
+  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. -->
+
+# xlnet-base-cased-HU-comple
+
+This model is a fine-tuned version of [xlnet-base-cased](https://huggingface.co/xlnet-base-cased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.9240
+- Accuracy: 0.8050
+- F1: 0.7619
+- Precision: 0.7568
+- Recall: 0.7671
+
+## 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: 16
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     | Precision | Recall |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
+| 0.6952        | 1.0   | 90   | 0.6760          | 0.5933   | 0.0    | 0.0       | 0.0    |
+| 0.694         | 2.0   | 180  | 0.6782          | 0.5933   | 0.0    | 0.0       | 0.0    |
+| 0.6856        | 3.0   | 270  | 0.6781          | 0.5933   | 0.0    | 0.0       | 0.0    |
+| 0.6868        | 4.0   | 360  | 0.7132          | 0.5933   | 0.0    | 0.0       | 0.0    |
+| 0.6353        | 5.0   | 450  | 0.6486          | 0.6657   | 0.6685 | 0.5602    | 0.8288 |
+| 0.5003        | 6.0   | 540  | 0.5151          | 0.7799   | 0.7189 | 0.7481    | 0.6918 |
+| 0.3585        | 7.0   | 630  | 0.5237          | 0.7660   | 0.7290 | 0.6890    | 0.7740 |
+| 0.2167        | 8.0   | 720  | 0.7817          | 0.7883   | 0.7226 | 0.7734    | 0.6781 |
+| 0.1643        | 9.0   | 810  | 0.8763          | 0.7939   | 0.7597 | 0.7222    | 0.8014 |
+| 0.135         | 10.0  | 900  | 0.9240          | 0.8050   | 0.7619 | 0.7568    | 0.7671 |
+
+
+### Framework versions
+
+- Transformers 4.43.0.dev0
+- Pytorch 2.0.1+cu117
+- Datasets 2.19.1
+- Tokenizers 0.19.1

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