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---
license: apache-2.0
base_model: distilbert/distilroberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: distilroberta_base_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. -->
# distilroberta_base_twitter
This model is a fine-tuned version of [distilbert/distilroberta-base](https://huggingface.co/distilbert/distilroberta-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4812
- Accuracy: 0.7721
- F1 Macro: 0.7373
- F1 Micro: 0.7721
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 0.4863 | 0.37 | 50 | 0.4848 | 0.7583 | 0.7216 | 0.7583 |
| 0.4736 | 0.74 | 100 | 0.4862 | 0.7629 | 0.7079 | 0.7629 |
| 0.463 | 1.1 | 150 | 0.4935 | 0.7739 | 0.7356 | 0.7739 |
| 0.4703 | 1.47 | 200 | 0.4812 | 0.7721 | 0.7373 | 0.7721 |
| 0.4537 | 1.84 | 250 | 0.4855 | 0.7665 | 0.7305 | 0.7665 |
| 0.4206 | 2.21 | 300 | 0.4880 | 0.7675 | 0.7283 | 0.7675 |
| 0.4561 | 2.57 | 350 | 0.4913 | 0.7629 | 0.7299 | 0.7629 |
| 0.3738 | 2.94 | 400 | 0.4950 | 0.7702 | 0.7359 | 0.7702 |
### Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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