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# spanbert-base-cased-finetuned-slot_fill

This model is a fine-tuned version of [SpanBERT/spanbert-base-cased](https://huggingface.co/SpanBERT/spanbert-base-cased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5806
- Precision: 0.6222
- Recall: 0.3415
- F1: 0.4409
- Accuracy: 0.8914

## 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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
| No log        | 1.0   | 18   | 0.8888          | 0.7143    | 0.3049 | 0.4274 | 0.8737   |
| No log        | 2.0   | 36   | 0.7158          | 0.7143    | 0.3049 | 0.4274 | 0.8737   |
| No log        | 3.0   | 54   | 0.6283          | 0.7143    | 0.3049 | 0.4274 | 0.8737   |
| No log        | 4.0   | 72   | 0.5922          | 0.7143    | 0.3049 | 0.4274 | 0.8737   |
| No log        | 5.0   | 90   | 0.5806          | 0.6222    | 0.3415 | 0.4409 | 0.8914   |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0

{"tags": ["generated_from_trainer"], "metrics": ["precision", "recall", "f1", "accuracy"], "base_model": "SpanBERT/spanbert-base-cased", "model-index": [{"name": "spanbert-base-cased-finetuned-slot_fill", "results": []}]}
transformers tensorboard safetensors bert token-classification generated_from_trainer base_model:SpanBERT/spanbert-base-cased autotrain_compatible endpoints_compatible region:us