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---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: distilbert-training-4
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. -->
# distilbert-training-4
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: 0.0316
- Accuracy: 0.9944
- Precision: 0.9955
- Recall: 0.9822
- F1: 0.9888
## 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: 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: 4
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log | 0.5 | 262 | 0.0957 | 0.9817 | 0.9562 | 0.9711 | 0.9636 |
| No log | 1.0 | 524 | 0.0390 | 0.9939 | 0.9977 | 0.9778 | 0.9877 |
| 0.1008 | 1.5 | 786 | 0.0361 | 0.9944 | 0.9955 | 0.9822 | 0.9888 |
| 0.1008 | 2.0 | 1048 | 0.0385 | 0.9922 | 0.9866 | 0.9822 | 0.9844 |
| 0.0331 | 2.5 | 1310 | 0.0270 | 0.9956 | 0.9977 | 0.9844 | 0.9911 |
| 0.0331 | 2.99 | 1572 | 0.0358 | 0.9939 | 0.9955 | 0.98 | 0.9877 |
| 0.0151 | 3.49 | 1834 | 0.0292 | 0.9956 | 0.9955 | 0.9867 | 0.9911 |
| 0.0151 | 3.99 | 2096 | 0.0316 | 0.9944 | 0.9955 | 0.9822 | 0.9888 |
### Framework versions
- Transformers 4.33.1
- Pytorch 2.2.0.dev20230913+cu121
- Tokenizers 0.13.3
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