metadata
library_name: transformers
language:
- spa
license: mit
base_model: diarizers-community/speaker-segmentation-fine-tuned-callhome-spa
tags:
- speaker-diarization
- speaker-segmentation
- generated_from_trainer
datasets:
- diarizers-community/callhome
model-index:
- name: speaker-segmentation-fine-tuned-callhome-spa
results: []
speaker-segmentation-fine-tuned-callhome-spa
This model is a fine-tuned version of diarizers-community/speaker-segmentation-fine-tuned-callhome-spa on the diarizers-community/callhome dataset. It achieves the following results on the evaluation set:
- Loss: 0.3513
- Der: 0.2029
- False Alarm: 0.1480
- Missed Detection: 0.0549
- Confusion: 0.0000
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: 0.001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Der | False Alarm | Missed Detection | Confusion |
|---|---|---|---|---|---|---|---|
| 0.3117 | 1.0 | 281 | 0.3448 | 0.2096 | 0.1526 | 0.0545 | 0.0024 |
| 0.2973 | 2.0 | 562 | 0.3260 | 0.1961 | 0.1359 | 0.0601 | 0.0001 |
| 0.2937 | 3.0 | 843 | 0.3413 | 0.2027 | 0.1468 | 0.0555 | 0.0004 |
| 0.2953 | 4.0 | 1124 | 0.3466 | 0.2023 | 0.1467 | 0.0555 | 0.0000 |
| 0.2725 | 5.0 | 1405 | 0.3513 | 0.2029 | 0.1480 | 0.0549 | 0.0000 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.1
- Datasets 3.0.1
- Tokenizers 0.20.0