|
--- |
|
language: |
|
- jpn |
|
license: apache-2.0 |
|
base_model: openai/whisper-small |
|
tags: |
|
- speaker-diarization |
|
- speaker-segmentation |
|
- generated_from_trainer |
|
datasets: |
|
- diarizers-community/callhome |
|
model-index: |
|
- name: speaker-segmentation-fine-tuned-callhome-jpn |
|
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. --> |
|
|
|
# speaker-segmentation-fine-tuned-callhome-jpn |
|
|
|
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the diarizers-community/callhome dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.7482 |
|
- Der: 0.2201 |
|
- False Alarm: 0.0465 |
|
- Missed Detection: 0.1319 |
|
- Confusion: 0.0417 |
|
|
|
## 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: 32 |
|
- eval_batch_size: 32 |
|
- 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 | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:-----------:|:----------------:|:---------:| |
|
| 0.5488 | 1.0 | 328 | 0.7565 | 0.2280 | 0.0461 | 0.1355 | 0.0465 | |
|
| 0.475 | 2.0 | 656 | 0.7596 | 0.2220 | 0.0467 | 0.1334 | 0.0419 | |
|
| 0.4734 | 3.0 | 984 | 0.7531 | 0.2215 | 0.0437 | 0.1364 | 0.0414 | |
|
| 0.4535 | 4.0 | 1312 | 0.7468 | 0.2194 | 0.0462 | 0.1323 | 0.0409 | |
|
| 0.4764 | 5.0 | 1640 | 0.7482 | 0.2201 | 0.0465 | 0.1319 | 0.0417 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.41.0 |
|
- Pytorch 2.3.0+cu121 |
|
- Datasets 2.19.1 |
|
- Tokenizers 0.19.1 |
|
|
