--- library_name: transformers license: apache-2.0 base_model: sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2 tags: - generated_from_trainer metrics: - precision - recall - f1 model-index: - name: fine-tuned-distilbert-autofill results: [] --- # fine-tuned-distilbert-autofill This model is a fine-tuned version of [sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2](https://huggingface.co/sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.2367 - Precision: 0.9484 - Recall: 0.9473 - F1: 0.9473 - Confusion Matrix: [[ 94 5 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0] [ 14 44 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 0 0 130 0 0 0 0 0 0 0 0 0 0 0 0 0 9] [ 0 0 0 33 0 0 0 0 0 0 0 0 0 0 2 0 0] [ 0 0 2 0 64 0 0 0 0 0 3 0 0 0 0 0 7] [ 0 0 0 0 0 53 0 0 0 0 0 0 0 0 2 0 0] [ 0 0 0 0 0 0 37 1 0 0 0 0 0 0 0 0 3] [ 0 0 0 0 0 0 4 35 0 0 0 0 0 0 0 0 2] [ 1 0 0 0 0 1 0 0 43 0 0 0 0 0 2 0 0] [ 0 0 0 0 0 0 0 0 0 31 0 0 0 0 1 0 0] [ 0 0 0 0 2 0 0 2 0 0 10 0 0 0 0 0 0] [ 0 0 0 0 0 0 0 1 0 0 1 16 0 0 0 0 0] [ 0 0 0 0 0 0 0 0 0 1 0 0 5 0 0 0 0] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0] [ 0 0 0 1 0 0 1 0 0 0 0 0 0 0 73 0 0] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0] [ 1 0 9 1 4 0 0 0 2 0 2 0 1 2 1 0 977]] ## 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: 5e-05 - 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 - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Confusion Matrix | |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------:| | 0.7726 | 1.0 | 987 | 0.3096 | 0.8920 | 0.9141 | 0.8988 | [[100 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 58 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 0 0 129 0 0 0 0 0 0 0 0 0 0 0 0 0 10] [ 0 0 0 32 0 0 0 0 1 1 0 0 0 0 0 0 1] [ 0 0 4 0 63 0 0 0 0 0 0 0 0 0 0 0 9] [ 0 0 0 0 0 52 0 0 0 2 0 0 0 0 0 0 1] [ 0 0 0 0 0 0 36 0 0 0 2 0 0 0 0 0 3] [ 0 0 0 0 0 0 2 33 0 0 4 0 0 0 0 0 2] [ 1 0 0 0 0 1 0 0 43 2 0 0 0 0 0 0 0] [ 0 0 0 0 0 0 0 0 0 32 0 0 0 0 0 0 0] [ 0 0 0 0 2 0 0 0 0 0 12 0 0 0 0 0 0] [ 0 0 0 0 0 0 4 0 0 0 1 13 0 0 0 0 0] [ 0 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0] [ 0 0 0 0 0 0 0 0 0 6 0 0 0 0 0 0 0] [ 0 0 0 0 0 0 1 0 1 2 0 0 0 0 71 0 0] [ 0 0 0 0 2 0 0 0 0 1 0 0 0 0 0 0 0] [ 1 0 7 1 5 0 0 0 1 3 1 0 0 0 1 0 980]] | | 0.2616 | 2.0 | 1974 | 0.2645 | 0.9356 | 0.9273 | 0.9179 | [[ 99 0 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0] [ 43 7 5 0 0 0 0 0 0 0 0 0 0 0 0 0 3] [ 0 0 128 0 0 0 0 0 0 0 0 0 0 0 0 0 11] [ 0 0 0 33 0 0 0 0 1 0 0 0 0 0 0 0 1] [ 0 0 0 0 64 0 0 0 0 0 0 0 0 0 0 0 12] [ 0 0 0 1 0 53 0 0 0 0 0 0 0 0 0 0 1] [ 0 0 0 0 0 0 36 2 0 0 0 0 0 0 0 0 3] [ 0 0 0 0 0 0 3 36 0 0 0 0 0 0 0 0 2] [ 1 0 0 0 0 2 0 0 43 0 0 0 0 0 0 0 1] [ 0 0 0 1 0 0 0 0 0 31 0 0 0 0 0 0 0] [ 0 0 0 0 2 0 0 3 0 0 9 0 0 0 0 0 0] [ 0 0 0 0 0 0 1 3 0 0 1 13 0 0 0 0 0] [ 0 0 0 0 0 0 0 0 0 1 0 0 5 0 0 0 0] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0] [ 0 0 0 1 0 0 1 0 1 1 0 0 0 0 71 0 0] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0] [ 1 0 6 1 3 0 0 0 1 0 2 0 1 2 1 0 982]] | | 0.1814 | 3.0 | 2961 | 0.2332 | 0.9437 | 0.9422 | 0.9420 | [[ 94 5 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0] [ 15 43 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 0 0 127 0 1 0 0 0 0 0 0 0 0 0 0 0 11] [ 0 0 0 34 0 0 0 0 0 0 0 0 0 0 0 0 1] [ 0 0 1 0 63 0 0 0 0 0 2 0 0 0 0 0 10] [ 0 0 0 1 0 52 0 0 0 1 1 0 0 0 0 0 0] [ 0 0 0 0 0 0 37 1 0 0 0 0 0 0 0 0 3] [ 0 0 0 0 0 0 4 35 0 0 0 0 0 0 0 0 2] [ 1 0 0 0 0 1 0 0 43 2 0 0 0 0 0 0 0] [ 0 0 0 1 0 0 0 0 0 31 0 0 0 0 0 0 0] [ 0 0 0 0 2 0 0 2 0 0 10 0 0 0 0 0 0] [ 0 0 0 0 0 0 2 2 0 0 1 13 0 0 0 0 0] [ 0 0 0 0 0 0 0 0 0 1 0 0 5 0 0 0 0] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0] [ 0 0 0 1 0 0 1 0 0 1 0 0 1 0 71 0 0] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0] [ 1 0 8 1 4 0 0 1 1 0 2 0 1 2 1 0 978]] | | 0.1248 | 4.0 | 3948 | 0.2255 | 0.9501 | 0.9479 | 0.9482 | [[ 95 4 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0] [ 13 45 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 0 0 130 0 0 0 0 0 0 0 0 0 0 0 0 0 9] [ 0 0 0 33 0 0 0 0 0 0 0 0 0 0 2 0 0] [ 0 0 2 0 65 0 0 0 0 0 4 0 0 0 0 0 5] [ 0 0 0 0 0 52 0 0 0 0 1 0 0 0 2 0 0] [ 0 0 0 0 0 0 38 0 0 0 0 0 0 0 0 0 3] [ 0 0 0 0 0 0 5 34 0 0 0 0 0 0 0 0 2] [ 1 0 0 0 0 1 0 0 43 0 0 0 0 0 2 0 0] [ 0 0 0 0 0 0 0 0 1 30 0 0 0 0 1 0 0] [ 0 0 0 0 2 0 2 0 0 0 10 0 0 0 0 0 0] [ 0 0 0 0 0 0 0 1 0 0 1 16 0 0 0 0 0] [ 0 0 0 0 0 0 0 0 0 1 0 0 5 0 0 0 0] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0] [ 0 0 0 1 0 0 1 0 0 0 0 0 0 0 73 0 0] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0] [ 1 0 9 1 4 0 0 0 2 0 2 0 1 2 1 0 977]] | | 0.1032 | 5.0 | 4935 | 0.2367 | 0.9484 | 0.9473 | 0.9473 | [[ 94 5 0 0 0 0 0 0 0 0 0 0 0 0 1 0 0] [ 14 44 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0] [ 0 0 130 0 0 0 0 0 0 0 0 0 0 0 0 0 9] [ 0 0 0 33 0 0 0 0 0 0 0 0 0 0 2 0 0] [ 0 0 2 0 64 0 0 0 0 0 3 0 0 0 0 0 7] [ 0 0 0 0 0 53 0 0 0 0 0 0 0 0 2 0 0] [ 0 0 0 0 0 0 37 1 0 0 0 0 0 0 0 0 3] [ 0 0 0 0 0 0 4 35 0 0 0 0 0 0 0 0 2] [ 1 0 0 0 0 1 0 0 43 0 0 0 0 0 2 0 0] [ 0 0 0 0 0 0 0 0 0 31 0 0 0 0 1 0 0] [ 0 0 0 0 2 0 0 2 0 0 10 0 0 0 0 0 0] [ 0 0 0 0 0 0 0 1 0 0 1 16 0 0 0 0 0] [ 0 0 0 0 0 0 0 0 0 1 0 0 5 0 0 0 0] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0] [ 0 0 0 1 0 0 1 0 0 0 0 0 0 0 73 0 0] [ 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 3 0] [ 1 0 9 1 4 0 0 0 2 0 2 0 1 2 1 0 977]] | ### Framework versions - Transformers 4.44.2 - Pytorch 2.1.2 - Datasets 2.19.2 - Tokenizers 0.19.1