---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
model-index:
- name: my_model
  results: []
---

<!-- 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. -->

# my_model

This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 5.9953
- Start Accuracy: 0.5270
- End Accuracy: 0.5270
- Overall Accuracy: 0.5270
- Start Precision: 0.2548
- End Precision: 0.2696
- Start Recall: 0.2307
- End Recall: 0.2805
- Start F1 Score: 0.2338
- End F1 Score: 0.2644

## 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: 1e-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: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Start Accuracy | End Accuracy | Overall Accuracy | Start Precision | End Precision | Start Recall | End Recall | Start F1 Score | End F1 Score |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:------------:|:----------------:|:---------------:|:-------------:|:------------:|:----------:|:--------------:|:------------:|
| 0.0302        | 1.0   | 22   | 6.1169          | 0.5405         | 0.4865       | 0.5135           | 0.2951          | 0.2569        | 0.2669       | 0.2371     | 0.2732         | 0.2331       |
| 0.0331        | 2.0   | 44   | 6.1384          | 0.4730         | 0.4730       | 0.4730           | 0.2056          | 0.2529        | 0.1692       | 0.2470     | 0.1801         | 0.2376       |
| 0.0332        | 3.0   | 66   | 6.0663          | 0.5135         | 0.5135       | 0.5135           | 0.2168          | 0.2434        | 0.1975       | 0.2619     | 0.1974         | 0.2446       |
| 0.0341        | 4.0   | 88   | 6.0363          | 0.5270         | 0.5270       | 0.5270           | 0.2548          | 0.2696        | 0.2307       | 0.2805     | 0.2338         | 0.2644       |
| 0.0213        | 5.0   | 110  | 5.9953          | 0.5270         | 0.5270       | 0.5270           | 0.2548          | 0.2696        | 0.2307       | 0.2805     | 0.2338         | 0.2644       |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2