roberta_emergency
This model is a fine-tuned version of bertin-project/bertin-roberta-base-spanish. It achieves the following results on the evaluation set:
- Loss: 0.6280
- Accuracy: 0.7773
Model description
This checkpoint classifies emergency transcribed calls into 3 labels: [CLAVE ROJA, CLAVE NARANJA, CLAVE AMARILLA]. Add some text to see the checkpoint's responses.
Intended uses & limitations
Under privacy agreement.
Training and evaluation data
Training data used has been provided by the ECU 911 service under a strict confidentiality agreement.
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 2e-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: 2
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.6674 | 1.0 | 559 | 0.6323 | 0.7630 |
0.5059 | 2.0 | 1118 | 0.6280 | 0.7773 |
Framework versions
- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
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Model tree for UDA-LIDI/roberta_emergency_classification
Base model
bertin-project/bertin-roberta-base-spanish