End of training

README.md

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+---
+license: mit
+base_model: Mikask/bdc2024-tpg
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: bdc2024-tpg-2
+  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. -->
+
+# bdc2024-tpg-2
+
+This model is a fine-tuned version of [Mikask/bdc2024-tpg](https://huggingface.co/Mikask/bdc2024-tpg) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0953
+- Accuracy: 0.9825
+- Balanced Accuracy: 0.9863
+- Precision: 0.9832
+- Recall: 0.9825
+- F1: 0.9826
+
+## 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: 6e-06
+- 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: linear
+- num_epochs: 3
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Balanced Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------------:|:---------:|:------:|:------:|
+| 0.0781        | 1.0   | 900  | 0.0990          | 0.9803   | 0.9779            | 0.9810    | 0.9803 | 0.9804 |
+| 0.0228        | 2.0   | 1800 | 0.0925          | 0.9782   | 0.9752            | 0.9788    | 0.9782 | 0.9782 |
+| 0.017         | 3.0   | 2700 | 0.0953          | 0.9825   | 0.9863            | 0.9832    | 0.9825 | 0.9826 |
+
+
+### Framework versions
+
+- Transformers 4.33.1
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.2
+- Tokenizers 0.13.3