--- license: apache-2.0 base_model: distilbert-base-uncased tags: - generated_from_trainer metrics: - accuracy - f1 - precision - recall model-index: - name: distilbert-base-uncased-english-cefr-lexical-evaluation-ep-v3 results: [] --- # distilbert-base-uncased-english-cefr-lexical-evaluation-ep-v3 This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset. It achieves the following results on the evaluation set: - Loss: 1.6313 - Accuracy: 0.6020 - F1: 0.6038 - Precision: 0.6142 - Recall: 0.6020 ## 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: 0.0001 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - num_epochs: 4 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| | 1.3952 | 1.0 | 346 | 1.4844 | 0.4345 | 0.4087 | 0.4461 | 0.4345 | | 1.0574 | 2.0 | 692 | 1.2710 | 0.5322 | 0.5369 | 0.5575 | 0.5322 | | 0.438 | 3.0 | 1038 | 1.4605 | 0.5590 | 0.5593 | 0.5751 | 0.5590 | | 0.0248 | 4.0 | 1384 | 1.8197 | 0.5720 | 0.5735 | 0.5801 | 0.5720 | ### Framework versions - Transformers 4.31.0 - Pytorch 2.0.1+cu118 - Datasets 2.13.1 - Tokenizers 0.13.3