distilbert-base-multilingual-cased-finetuned-with-spanish-tweets-clf-cleaned-ds
This model is a fine-tuned version of distilbert-base-multilingual-cased on the dataset dataset. It achieves the following results on the evaluation set:
- Loss: 1.5095
- Accuracy: 0.5950
- F1: 0.5960
- Precision: 0.6036
- Recall: 0.5949
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: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4.0
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
---|---|---|---|---|---|---|---|
1.018 | 1.0 | 543 | 0.9421 | 0.5536 | 0.4949 | 0.5347 | 0.5146 |
0.8079 | 2.0 | 1086 | 0.9275 | 0.5957 | 0.5751 | 0.5921 | 0.5725 |
0.521 | 3.0 | 1629 | 1.1208 | 0.6033 | 0.6050 | 0.6146 | 0.6023 |
0.3225 | 4.0 | 2172 | 1.5095 | 0.5950 | 0.5960 | 0.6036 | 0.5949 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1
- Datasets 2.8.0
- Tokenizers 0.13.2
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Evaluation results
- Accuracy on datasetself-reported0.595
- F1 on datasetself-reported0.596
- Precision on datasetself-reported0.604
- Recall on datasetself-reported0.595