AntoineD/MiniLM_classification_tools_fr

1---2license: mit3base_model: microsoft/Multilingual-MiniLM-L12-H3844tags:5- generated_from_trainer6metrics:7- accuracy8model-index:9- name: MiniLM_classification_tools_fr10  results: []11---12 13<!-- This model card has been generated automatically according to the information the Trainer had access to. You14should probably proofread and complete it, then remove this comment. -->15 16# MiniLM_classification_tools_fr17 18This model is a fine-tuned version of [microsoft/Multilingual-MiniLM-L12-H384](https://huggingface.co/microsoft/Multilingual-MiniLM-L12-H384) on the None dataset.19It achieves the following results on the evaluation set:20- Loss: 0.769421- Accuracy: 0.7522- Learning Rate: 0.000023 24## Model description25 26More information needed27 28## Intended uses & limitations29 30More information needed31 32## Training and evaluation data33 34More information needed35 36## Training procedure37 38### Training hyperparameters39 40The following hyperparameters were used during training:41- learning_rate: 0.000142- train_batch_size: 2443- eval_batch_size: 19244- seed: 4245- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-0846- lr_scheduler_type: linear47- num_epochs: 6048 49### Training results50 51| Training Loss | Epoch | Step | Validation Loss | Accuracy | Rate   |52|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|53| No log        | 1.0   | 7    | 2.0620          | 0.35     | 0.0001 |54| No log        | 2.0   | 14   | 1.9515          | 0.425    | 0.0001 |55| No log        | 3.0   | 21   | 1.7736          | 0.45     | 0.0001 |56| No log        | 4.0   | 28   | 1.6055          | 0.475    | 0.0001 |57| No log        | 5.0   | 35   | 1.5108          | 0.5      | 0.0001 |58| No log        | 6.0   | 42   | 1.4074          | 0.45     | 9e-05  |59| No log        | 7.0   | 49   | 1.3848          | 0.475    | 0.0001 |60| No log        | 8.0   | 56   | 1.2533          | 0.625    | 0.0001 |61| No log        | 9.0   | 63   | 1.2463          | 0.525    | 0.0001 |62| No log        | 10.0  | 70   | 1.1593          | 0.6      | 0.0001 |63| No log        | 11.0  | 77   | 1.1637          | 0.6      | 0.0001 |64| No log        | 12.0  | 84   | 1.0900          | 0.625    | 8e-05  |65| No log        | 13.0  | 91   | 0.9577          | 0.7      | 0.0001 |66| No log        | 14.0  | 98   | 0.9465          | 0.675    | 0.0001 |67| No log        | 15.0  | 105  | 0.9255          | 0.675    | 0.0001 |68| No log        | 16.0  | 112  | 0.8836          | 0.675    | 0.0001 |69| No log        | 17.0  | 119  | 0.8307          | 0.675    | 0.0001 |70| No log        | 18.0  | 126  | 0.8335          | 0.725    | 7e-05  |71| No log        | 19.0  | 133  | 0.8469          | 0.625    | 0.0001 |72| No log        | 20.0  | 140  | 0.7384          | 0.75     | 0.0001 |73| No log        | 21.0  | 147  | 0.7330          | 0.775    | 0.0001 |74| No log        | 22.0  | 154  | 0.7811          | 0.775    | 0.0001 |75| No log        | 23.0  | 161  | 0.6857          | 0.8      | 0.0001 |76| No log        | 24.0  | 168  | 0.6733          | 0.825    | 6e-05  |77| No log        | 25.0  | 175  | 0.6510          | 0.85     | 0.0001 |78| No log        | 26.0  | 182  | 0.6363          | 0.85     | 0.0001 |79| No log        | 27.0  | 189  | 0.6101          | 0.875    | 0.0001 |80| No log        | 28.0  | 196  | 0.6434          | 0.8      | 0.0001 |81| No log        | 29.0  | 203  | 0.6644          | 0.775    | 0.0001 |82| No log        | 30.0  | 210  | 0.7162          | 0.75     | 5e-05  |83| No log        | 31.0  | 217  | 0.7422          | 0.775    | 0.0000 |84| No log        | 32.0  | 224  | 0.7120          | 0.775    | 0.0000 |85| No log        | 33.0  | 231  | 0.6296          | 0.8      | 0.0000 |86| No log        | 34.0  | 238  | 0.6522          | 0.775    | 0.0000 |87| No log        | 35.0  | 245  | 0.7636          | 0.75     | 0.0000 |88| No log        | 36.0  | 252  | 0.7703          | 0.75     | 4e-05  |89| No log        | 37.0  | 259  | 0.7694          | 0.75     | 0.0000 |90 91 92### Framework versions93 94- Transformers 4.34.095- Pytorch 2.0.1+cu11796- Datasets 2.14.597- Tokenizers 0.14.198