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# distilbert_system_B

This model is a fine-tuned version of [distilbert-base-cased](https://huggingface.co/distilbert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0293
- Precision: 0.9456
- Recall: 0.9531
- F1: 0.9493
- Accuracy: 0.9931

## 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: 32
- eval_batch_size: 32
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:--------:|
| 0.0134        | 1.0   | 8205  | 0.0208          | 0.9466    | 0.9488 | 0.9477 | 0.9929   |
| 0.0067        | 2.0   | 16410 | 0.0237          | 0.9453    | 0.9528 | 0.9490 | 0.9931   |
| 0.0031        | 3.0   | 24615 | 0.0293          | 0.9456    | 0.9531 | 0.9493 | 0.9931   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
{"language": ["en"], "license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["Babelscape/multinerd"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "distilbert-base-cased", "model-index": [{"name": "distilbert_system_B", "results": []}]}
transformers tensorboard safetensors distilbert token-classification generated_from_trainer en dataset:Babelscape/multinerd base_model:distilbert-base-cased license:apache-2.0 autotrain_compatible endpoints_compatible region:us