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---
license: apache-2.0
base_model: distilbert/distilbert-base-uncased
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilbert_base_uncased_twitter
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_twitter
This model is a fine-tuned version of [distilbert/distilbert-base-uncased](https://huggingface.co/distilbert/distilbert-base-uncased) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4864
- Accuracy: 0.7665
- F1 Macro: 0.7130
- F1 Micro: 0.7665
## 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: 32
- eval_batch_size: 32
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Micro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 0.4671 | 0.37 | 50 | 0.4990 | 0.7665 | 0.7214 | 0.7665 |
| 0.4724 | 0.74 | 100 | 0.4864 | 0.7665 | 0.7130 | 0.7665 |
| 0.4569 | 1.1 | 150 | 0.4924 | 0.7619 | 0.7171 | 0.7619 |
| 0.4577 | 1.47 | 200 | 0.4881 | 0.7675 | 0.7357 | 0.7675 |
| 0.4438 | 1.84 | 250 | 0.4902 | 0.7638 | 0.7222 | 0.7638 |
| 0.405 | 2.21 | 300 | 0.4901 | 0.7647 | 0.7211 | 0.7647 |
| 0.4308 | 2.57 | 350 | 0.4900 | 0.7693 | 0.7326 | 0.7693 |
| 0.3584 | 2.94 | 400 | 0.4931 | 0.7675 | 0.7288 | 0.7675 |
### Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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