Model save

README.md

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+---
+library_name: transformers
+license: mit
+base_model: xlnet/xlnet-large-cased
+tags:
+- generated_from_trainer
+metrics:
+- f1
+- accuracy
+model-index:
+- name: xlnet-large-cased-finetuned-augmentation-LUNAR-TAPT
+  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-large-cased-finetuned-augmentation-LUNAR-TAPT
+
+This model is a fine-tuned version of [xlnet/xlnet-large-cased](https://huggingface.co/xlnet/xlnet-large-cased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5259
+- F1: 0.8235
+- Roc Auc: 0.8652
+- Accuracy: 0.6073
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 100
+- num_epochs: 20
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
+| 0.3732        | 1.0   | 318  | 0.3677          | 0.6417 | 0.7249  | 0.4227   |
+| 0.291         | 2.0   | 636  | 0.2986          | 0.7666 | 0.8238  | 0.5426   |
+| 0.2296        | 3.0   | 954  | 0.2937          | 0.7774 | 0.8291  | 0.5552   |
+| 0.1332        | 4.0   | 1272 | 0.3269          | 0.7980 | 0.8559  | 0.5797   |
+| 0.0964        | 5.0   | 1590 | 0.3768          | 0.7977 | 0.8473  | 0.5505   |
+| 0.0618        | 6.0   | 1908 | 0.4196          | 0.7833 | 0.8416  | 0.5552   |
+| 0.0356        | 7.0   | 2226 | 0.4305          | 0.8041 | 0.8509  | 0.5726   |
+| 0.0214        | 8.0   | 2544 | 0.4510          | 0.8112 | 0.8482  | 0.5883   |
+| 0.0196        | 9.0   | 2862 | 0.4708          | 0.8118 | 0.8582  | 0.5970   |
+| 0.0111        | 10.0  | 3180 | 0.4950          | 0.8174 | 0.8590  | 0.5994   |
+| 0.0124        | 11.0  | 3498 | 0.5083          | 0.8094 | 0.8572  | 0.5852   |
+| 0.0079        | 12.0  | 3816 | 0.4904          | 0.8291 | 0.8646  | 0.6215   |
+| 0.0062        | 13.0  | 4134 | 0.5218          | 0.8155 | 0.8578  | 0.5954   |
+| 0.001         | 14.0  | 4452 | 0.5225          | 0.8194 | 0.8636  | 0.6073   |
+| 0.0024        | 15.0  | 4770 | 0.5248          | 0.8244 | 0.8646  | 0.6088   |
+| 0.0012        | 16.0  | 5088 | 0.5259          | 0.8235 | 0.8652  | 0.6073   |
+
+
+### Framework versions
+
+- Transformers 4.45.1
+- Pytorch 2.4.0
+- Datasets 3.0.1
+- Tokenizers 0.20.0

model.safetensors

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