UDA-LIDI/roberta_emergency_classification

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