pytorch distilbert text-classification transformers generated_from_trainer license:apache-2.0 model-index
---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert-base-multilingual-cased-cv-studio_name-pooler
  results: []
---

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# distilbert-base-multilingual-cased-cv-studio_name-pooler

This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3751
- Accuracy: 0.6846
- F1 Micro: 0.6846
- F1 Macro: 0.4355
- Precision Micro: 0.6846
- Recall Micro: 0.6846

## 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: 12
- 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_steps: 20
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy | F1 Micro | F1 Macro | Precision Micro | Recall Micro |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:--------:|:---------------:|:------------:|
| 1.881         | 1.19  | 1000  | 1.6365          | 0.4948   | 0.4948   | 0.1438   | 0.4948          | 0.4948       |
| 1.2071        | 2.39  | 2000  | 1.2566          | 0.6444   | 0.6444   | 0.3257   | 0.6444          | 0.6444       |
| 0.9068        | 3.58  | 3000  | 1.1112          | 0.6945   | 0.6945   | 0.3995   | 0.6945          | 0.6945       |
| 0.7168        | 4.77  | 4000  | 1.0952          | 0.7053   | 0.7053   | 0.4334   | 0.7053          | 0.7053       |
| 0.5928        | 5.97  | 5000  | 1.1416          | 0.7116   | 0.7116   | 0.4505   | 0.7116          | 0.7116       |
| 0.4373        | 7.16  | 6000  | 1.2468          | 0.7064   | 0.7064   | 0.4499   | 0.7064          | 0.7064       |
| 0.2941        | 8.35  | 7000  | 1.4017          | 0.6997   | 0.6997   | 0.4473   | 0.6997          | 0.6997       |
| 0.2139        | 9.55  | 8000  | 1.5695          | 0.6973   | 0.6973   | 0.4433   | 0.6973          | 0.6973       |
| 0.1437        | 10.74 | 9000  | 1.7535          | 0.6953   | 0.6953   | 0.4387   | 0.6953          | 0.6953       |
| 0.1273        | 11.93 | 10000 | 1.9145          | 0.6937   | 0.6937   | 0.4405   | 0.6937          | 0.6937       |
| 0.1042        | 13.13 | 11000 | 2.0205          | 0.6893   | 0.6893   | 0.4370   | 0.6893          | 0.6893       |
| 0.07          | 14.32 | 12000 | 2.1489          | 0.6881   | 0.6881   | 0.4372   | 0.6881          | 0.6881       |
| 0.0526        | 15.51 | 13000 | 2.2252          | 0.6874   | 0.6874   | 0.4349   | 0.6874          | 0.6874       |
| 0.0427        | 16.71 | 14000 | 2.3141          | 0.6877   | 0.6877   | 0.4360   | 0.6877          | 0.6877       |
| 0.0482        | 17.9  | 15000 | 2.3349          | 0.6810   | 0.6810   | 0.4320   | 0.6810          | 0.6810       |
| 0.042         | 19.09 | 16000 | 2.3751          | 0.6846   | 0.6846   | 0.4355   | 0.6846          | 0.6846       |


### Framework versions

- Transformers 4.20.1
- Pytorch 1.8.1+cu111
- Datasets 1.6.2
- Tokenizers 0.12.1
