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README.md
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---
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license: apache-2.0
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base_model: distilbert-base-uncased
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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model-index:
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- name: distilbert-base-uncased-DIALOCONAN-WIKI-CLS
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# distilbert-base-uncased-DIALOCONAN-WIKI-CLS
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4006
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- Precision: 0.6306
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- Recall: 0.6327
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- F1: 0.6316
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- Accuracy: 0.9460
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 3e-05
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- train_batch_size: 4
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- eval_batch_size: 4
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| 0.3444 | 1.0 | 2500 | 0.3613 | 0.6877 | 0.6910 | 0.6884 | 0.9171 |
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| 0.2104 | 2.0 | 5000 | 0.3773 | 0.7006 | 0.7035 | 0.7017 | 0.9344 |
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| 0.1061 | 3.0 | 7500 | 0.3585 | 0.7054 | 0.7074 | 0.7063 | 0.9404 |
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| 0.0669 | 4.0 | 10000 | 0.4002 | 0.6291 | 0.6309 | 0.6299 | 0.9434 |
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| 0.0327 | 5.0 | 12500 | 0.4006 | 0.6306 | 0.6327 | 0.6316 | 0.9460 |
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### Framework versions
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- Transformers 4.42.4
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- Pytorch 2.3.1+cu121
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- Datasets 2.21.0
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- Tokenizers 0.19.1
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