
<!-- 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. -->

# distilbert-base-uncased-finetuned-ner

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the fin dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1142
- Precision: 0.9825
- Recall: 0.8776
- F1: 0.9271
- Accuracy: 0.9852

## 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: 16
- eval_batch_size: 16
- 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   | 64   | 0.1589          | 0.9760    | 0.7422 | 0.8432 | 0.9752   |
| No log        | 2.0   | 128  | 0.1221          | 0.9731    | 0.7526 | 0.8488 | 0.9765   |
| No log        | 3.0   | 192  | 0.1142          | 0.9825    | 0.8776 | 0.9271 | 0.9852   |


### Framework versions

- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1

{"license": "apache-2.0", "tags": ["generated_from_trainer"], "datasets": ["fin"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "distilbert-base-uncased", "model-index": [{"name": "distilbert-base-uncased-finetuned-ner", "results": [{"task": {"type": "token-classification", "name": "Token Classification"}, "dataset": {"name": "fin", "type": "fin", "config": "fin", "split": "validation", "args": "fin"}, "metrics": [{"type": "precision", "value": 0.9825072886297376, "name": "Precision"}, {"type": "recall", "value": 0.8776041666666666, "name": "Recall"}, {"type": "f1", "value": 0.9270976616231086, "name": "F1"}, {"type": "accuracy", "value": 0.9851503078594712, "name": "Accuracy"}]}]}]}
transformers tensorboard safetensors distilbert token-classification generated_from_trainer dataset:fin base_model:distilbert-base-uncased license:apache-2.0 model-index autotrain_compatible endpoints_compatible region:us