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---
license: apache-2.0
base_model: distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- f1
model-index:
- name: distilbert-base-uncased-Distilbert-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. -->
# distilbert-base-uncased-Distilbert-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: 0.7383
- F1: 0.6823
## 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: 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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 0.848 | 0.5015 | 500 | 0.7910 | 0.6663 |
| 0.7872 | 1.0030 | 1000 | 0.7383 | 0.6823 |
| 0.6766 | 1.5045 | 1500 | 0.7502 | 0.7054 |
| 0.6854 | 2.0060 | 2000 | 0.7424 | 0.7096 |
| 0.5239 | 2.5075 | 2500 | 0.9047 | 0.7219 |
| 0.525 | 3.0090 | 3000 | 0.8375 | 0.7221 |
| 0.3925 | 3.5105 | 3500 | 1.0093 | 0.7216 |
| 0.4061 | 4.0120 | 4000 | 1.1403 | 0.7245 |
| 0.2928 | 4.5135 | 4500 | 1.3150 | 0.6862 |
| 0.3055 | 5.0150 | 5000 | 1.3811 | 0.7101 |
| 0.2184 | 5.5165 | 5500 | 1.5753 | 0.6985 |
| 0.23 | 6.0181 | 6000 | 1.5571 | 0.7122 |
| 0.1705 | 6.5196 | 6500 | 1.6771 | 0.7155 |
| 0.1416 | 7.0211 | 7000 | 1.7773 | 0.7089 |
| 0.1085 | 7.5226 | 7500 | 1.9134 | 0.7124 |
| 0.1437 | 8.0241 | 8000 | 1.8510 | 0.7118 |
| 0.0967 | 8.5256 | 8500 | 2.0276 | 0.7074 |
| 0.0733 | 9.0271 | 9000 | 2.1793 | 0.7112 |
| 0.0671 | 9.5286 | 9500 | 2.1100 | 0.7118 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cpu
- Datasets 2.20.0
- Tokenizers 0.19.1
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