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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: results_distilbert-base-uncased
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. -->
# results_distilbert-base-uncased
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: 0.1696
- Accuracy: 0.9277
- Precision: 0.9364
- Recall: 0.9447
- F1: 0.9406
## 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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.6033 | 0.09 | 50 | 0.3599 | 0.8509 | 0.8622 | 0.8970 | 0.8792 |
| 0.3466 | 0.18 | 100 | 0.3466 | 0.8527 | 0.9638 | 0.7862 | 0.8660 |
| 0.2446 | 0.28 | 150 | 0.2166 | 0.9073 | 0.9293 | 0.9165 | 0.9229 |
| 0.2277 | 0.37 | 200 | 0.2014 | 0.9137 | 0.9153 | 0.9450 | 0.9299 |
| 0.2099 | 0.46 | 250 | 0.2183 | 0.9174 | 0.9090 | 0.9596 | 0.9336 |
| 0.2276 | 0.55 | 300 | 0.1927 | 0.9195 | 0.9275 | 0.9405 | 0.9340 |
| 0.21 | 0.64 | 350 | 0.1807 | 0.9254 | 0.9381 | 0.9387 | 0.9384 |
| 0.2009 | 0.74 | 400 | 0.1808 | 0.9236 | 0.9471 | 0.9254 | 0.9361 |
| 0.1816 | 0.83 | 450 | 0.1823 | 0.9238 | 0.9173 | 0.9607 | 0.9385 |
| 0.1728 | 0.92 | 500 | 0.1696 | 0.9277 | 0.9364 | 0.9447 | 0.9406 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2
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