transformers tensorboard safetensors distilbert token-classification generated_from_trainer dataset:hipe2020 model-index autotrain_compatible endpoints_compatible region:us
---
tags:
- generated_from_trainer
datasets:
- hipe2020
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: distilbert-base-uncased
  results:
  - task:
      name: Token Classification
      type: token-classification
    dataset:
      name: hipe2020
      type: hipe2020
      config: fr
      split: validation
      args: fr
    metrics:
    - name: Precision
      type: precision
      value: 0.0
    - name: Recall
      type: recall
      value: 0.0
    - name: F1
      type: f1
      value: 0.0
    - name: Accuracy
      type: accuracy
      value: 0.878272070662925
---

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# distilbert-base-uncased

This model was trained from scratch on the hipe2020 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5372
- Precision: 0.0
- Recall: 0.0
- F1: 0.0
- Accuracy: 0.8783

## 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: 2e-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: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1  | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
| No log        | 1.0   | 21   | 0.6196          | 0.0       | 0.0    | 0.0 | 0.8783   |
| No log        | 2.0   | 42   | 0.5704          | 0.0       | 0.0    | 0.0 | 0.8783   |
| No log        | 3.0   | 63   | 0.5372          | 0.0       | 0.0    | 0.0 | 0.8783   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
