End of training

README.md

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+---
+license: apache-2.0
+base_model: distilbert-base-uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: insuff_supported_arguments
+  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. -->
+
+# insuff_supported_arguments
+
+This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0000
+- Negative: {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 13620.0}
+- Positive: {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 6960.0}
+- Accuracy: 1.0
+- Macro avg: {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 20580.0}
+- Weighted avg: {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 20580.0}
+
+## 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: linear
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Negative                                                               | Positive                                                              | Accuracy | Macro avg                                                              | Weighted avg                                                           |
+|:-------------:|:-----:|:----:|:---------------:|:----------------------------------------------------------------------:|:---------------------------------------------------------------------:|:--------:|:----------------------------------------------------------------------:|:----------------------------------------------------------------------:|
+| 0.0           | 1.0   | 4628 | 0.0000          | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 13620.0} | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 6960.0} | 1.0      | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 20580.0} | {'precision': 1.0, 'recall': 1.0, 'f1-score': 1.0, 'support': 20580.0} |
+
+
+### Framework versions
+
+- Transformers 4.38.2
+- Pytorch 2.2.1+cu121
+- Datasets 2.17.1
+- Tokenizers 0.15.2