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---
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
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