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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-ep-v4
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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-ep-v4
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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: 1.9206
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- Accuracy: 0.6093
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- F1: 0.6095
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- Precision: 0.6174
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- Recall: 0.6093
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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: 8
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- eval_batch_size: 8
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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: 6
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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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| 1.2735 | 1.0 | 346 | 1.4207 | 0.4721 | 0.4451 | 0.4941 | 0.4721 |
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| 1.0356 | 2.0 | 692 | 1.2296 | 0.5380 | 0.5399 | 0.5786 | 0.5380 |
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| 0.3684 | 3.0 | 1038 | 1.6360 | 0.5590 | 0.5619 | 0.5712 | 0.5590 |
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| 0.1539 | 4.0 | 1384 | 2.1402 | 0.5844 | 0.5846 | 0.5901 | 0.5844 |
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| 0.2342 | 5.0 | 1730 | 2.4715 | 0.5807 | 0.5828 | 0.5915 | 0.5807 |
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| 0.0022 | 6.0 | 2076 | 2.4647 | 0.5742 | 0.5763 | 0.5802 | 0.5742 |
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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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