---
license: mit
base_model: microsoft/MiniLM-L12-H384-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: MiniLM_uncased_classification_tools_fr
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# MiniLM_uncased_classification_tools_fr

This model is a fine-tuned version of [microsoft/MiniLM-L12-H384-uncased](https://huggingface.co./microsoft/MiniLM-L12-H384-uncased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3165
- Accuracy: 0.925
- Learning Rate: 0.0

## 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: 24
- eval_batch_size: 192
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 60

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Rate   |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| No log        | 1.0   | 7    | 2.0607          | 0.35     | 0.0001 |
| No log        | 2.0   | 14   | 1.9111          | 0.425    | 0.0001 |
| No log        | 3.0   | 21   | 1.6543          | 0.45     | 0.0001 |
| No log        | 4.0   | 28   | 1.4578          | 0.525    | 0.0001 |
| No log        | 5.0   | 35   | 1.3136          | 0.65     | 0.0001 |
| No log        | 6.0   | 42   | 1.2160          | 0.7      | 9e-05  |
| No log        | 7.0   | 49   | 1.0786          | 0.725    | 0.0001 |
| No log        | 8.0   | 56   | 1.0171          | 0.675    | 0.0001 |
| No log        | 9.0   | 63   | 0.9491          | 0.7      | 0.0001 |
| No log        | 10.0  | 70   | 0.8773          | 0.75     | 0.0001 |
| No log        | 11.0  | 77   | 0.8019          | 0.75     | 0.0001 |
| No log        | 12.0  | 84   | 0.7436          | 0.775    | 8e-05  |
| No log        | 13.0  | 91   | 0.6747          | 0.825    | 0.0001 |
| No log        | 14.0  | 98   | 0.7357          | 0.775    | 0.0001 |
| No log        | 15.0  | 105  | 0.5386          | 0.85     | 0.0001 |
| No log        | 16.0  | 112  | 0.6222          | 0.85     | 0.0001 |
| No log        | 17.0  | 119  | 0.6284          | 0.85     | 0.0001 |
| No log        | 18.0  | 126  | 0.4489          | 0.9      | 7e-05  |
| No log        | 19.0  | 133  | 0.6431          | 0.85     | 0.0001 |
| No log        | 20.0  | 140  | 0.6064          | 0.85     | 0.0001 |
| No log        | 21.0  | 147  | 0.6948          | 0.825    | 0.0001 |
| No log        | 22.0  | 154  | 0.5535          | 0.85     | 0.0001 |
| No log        | 23.0  | 161  | 0.4672          | 0.875    | 0.0001 |
| No log        | 24.0  | 168  | 0.4797          | 0.875    | 6e-05  |
| No log        | 25.0  | 175  | 0.4908          | 0.9      | 0.0001 |
| No log        | 26.0  | 182  | 0.5879          | 0.85     | 0.0001 |
| No log        | 27.0  | 189  | 0.6601          | 0.85     | 0.0001 |
| No log        | 28.0  | 196  | 0.6036          | 0.85     | 0.0001 |
| No log        | 29.0  | 203  | 0.5495          | 0.85     | 0.0001 |
| No log        | 30.0  | 210  | 0.5135          | 0.85     | 5e-05  |
| No log        | 31.0  | 217  | 0.4767          | 0.875    | 0.0000 |
| No log        | 32.0  | 224  | 0.4431          | 0.9      | 0.0000 |
| No log        | 33.0  | 231  | 0.4681          | 0.875    | 0.0000 |
| No log        | 34.0  | 238  | 0.5612          | 0.85     | 0.0000 |
| No log        | 35.0  | 245  | 0.4495          | 0.9      | 0.0000 |
| No log        | 36.0  | 252  | 0.4384          | 0.9      | 4e-05  |
| No log        | 37.0  | 259  | 0.4378          | 0.875    | 0.0000 |
| No log        | 38.0  | 266  | 0.4104          | 0.875    | 0.0000 |
| No log        | 39.0  | 273  | 0.5060          | 0.875    | 0.0000 |
| No log        | 40.0  | 280  | 0.4756          | 0.875    | 0.0000 |
| No log        | 41.0  | 287  | 0.4558          | 0.875    | 0.0000 |
| No log        | 42.0  | 294  | 0.4458          | 0.9      | 3e-05  |
| No log        | 43.0  | 301  | 0.3969          | 0.875    | 0.0000 |
| No log        | 44.0  | 308  | 0.4762          | 0.875    | 0.0000 |
| No log        | 45.0  | 315  | 0.4891          | 0.875    | 0.0000 |
| No log        | 46.0  | 322  | 0.4460          | 0.9      | 0.0000 |
| No log        | 47.0  | 329  | 0.3892          | 0.925    | 0.0000 |
| No log        | 48.0  | 336  | 0.4267          | 0.9      | 2e-05  |
| No log        | 49.0  | 343  | 0.3327          | 0.9      | 0.0000 |
| No log        | 50.0  | 350  | 0.3225          | 0.925    | 0.0000 |
| No log        | 51.0  | 357  | 0.3223          | 0.925    | 0.0000 |
| No log        | 52.0  | 364  | 0.3136          | 0.95     | 0.0000 |
| No log        | 53.0  | 371  | 0.3109          | 0.925    | 0.0000 |
| No log        | 54.0  | 378  | 0.3142          | 0.9      | 1e-05  |
| No log        | 55.0  | 385  | 0.3168          | 0.925    | 0.0000 |
| No log        | 56.0  | 392  | 0.3163          | 0.925    | 0.0000 |
| No log        | 57.0  | 399  | 0.3174          | 0.925    | 5e-06  |
| No log        | 58.0  | 406  | 0.3185          | 0.925    | 0.0000 |
| No log        | 59.0  | 413  | 0.3168          | 0.925    | 0.0000 |
| No log        | 60.0  | 420  | 0.3165          | 0.925    | 0.0    |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.1