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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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- accuracy
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- f1
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- precision
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- recall
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model-index:
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- name: distilbert-base-uncased-english-cefr-lexical-evaluation-bs-v2
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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-english-cefr-lexical-evaluation-bs-v2
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This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.6208
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- Accuracy: 0.5876
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- F1: 0.5859
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- Precision: 0.5892
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- Recall: 0.5876
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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: 0.0001
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- train_batch_size: 16
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- eval_batch_size: 16
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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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- lr_scheduler_warmup_ratio: 0.1
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- num_epochs: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
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| 1.3819 | 1.0 | 173 | 1.3925 | 0.4859 | 0.4780 | 0.4752 | 0.4859 |
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| 1.0132 | 2.0 | 346 | 1.3560 | 0.5011 | 0.5008 | 0.5815 | 0.5011 |
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| 0.4879 | 3.0 | 519 | 1.4646 | 0.5510 | 0.5532 | 0.5612 | 0.5510 |
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| 0.1783 | 4.0 | 692 | 1.7720 | 0.5713 | 0.5705 | 0.5724 | 0.5713 |
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| 0.0539 | 5.0 | 865 | 1.9786 | 0.5634 | 0.5650 | 0.5701 | 0.5634 |
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### Framework versions
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- Transformers 4.31.0
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- Pytorch 2.0.1+cu118
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- Datasets 2.13.1
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- Tokenizers 0.13.3
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