| --- |
| library_name: transformers |
| tags: |
| - generated_from_trainer |
| model-index: |
| - name: pyannote_fine_tuning |
| 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. --> |
|
|
| # pyannote_fine_tuning |
|
|
| This model is a fine-tuned version of [](https://huggingface.co/) on an unknown dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.1283 |
| - Model Preparation Time: 0.0036 |
| - Der: 0.0490 |
| - False Alarm: 0.0309 |
| - Missed Detection: 0.0091 |
| - Confusion: 0.0090 |
|
|
| ## Model description |
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| More information needed |
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|
| ## Intended uses & limitations |
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| More information needed |
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| ## Training and evaluation data |
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| More information needed |
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| ## Training procedure |
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| ### Training hyperparameters |
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| 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 |
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|
| | Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Der | False Alarm | Missed Detection | Confusion | |
| |:-------------:|:-----:|:----:|:---------------:|:----------------------:|:------:|:-----------:|:----------------:|:---------:| |
| | No log | 1.0 | 21 | 0.1258 | 0.0036 | 0.0485 | 0.0287 | 0.0105 | 0.0093 | |
| | 0.228 | 2.0 | 42 | 0.1327 | 0.0036 | 0.0509 | 0.0300 | 0.0098 | 0.0112 | |
| | 0.1873 | 3.0 | 63 | 0.1280 | 0.0036 | 0.0496 | 0.0307 | 0.0092 | 0.0097 | |
| | 0.166 | 4.0 | 84 | 0.1280 | 0.0036 | 0.0487 | 0.0307 | 0.0091 | 0.0090 | |
| | 0.152 | 5.0 | 105 | 0.1283 | 0.0036 | 0.0490 | 0.0309 | 0.0091 | 0.0090 | |
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| ### Framework versions |
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|
| - Transformers 4.44.2 |
| - Pytorch 2.5.0+cu121 |
| - Datasets 3.1.0 |
| - Tokenizers 0.19.1 |
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|
