End of training

README.md

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+---
+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-eng
+  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-eng
+
+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: 0.4666
+- Der: 0.1827
+- False Alarm: 0.0590
+- Missed Detection: 0.0715
+- Confusion: 0.0522
+
+## 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: 10
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Der    | False Alarm | Missed Detection | Confusion |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:-----------:|:----------------:|:---------:|
+| 0.4224        | 1.0   | 181  | 0.4837          | 0.1939 | 0.0599      | 0.0764           | 0.0576    |
+| 0.409         | 2.0   | 362  | 0.4692          | 0.1884 | 0.0618      | 0.0724           | 0.0543    |
+| 0.3919        | 3.0   | 543  | 0.4700          | 0.1875 | 0.0638      | 0.0698           | 0.0540    |
+| 0.3693        | 4.0   | 724  | 0.4718          | 0.1848 | 0.0602      | 0.0714           | 0.0533    |
+| 0.358         | 5.0   | 905  | 0.4606          | 0.1810 | 0.0544      | 0.0754           | 0.0512    |
+| 0.355         | 6.0   | 1086 | 0.4631          | 0.1826 | 0.0638      | 0.0677           | 0.0512    |
+| 0.3563        | 7.0   | 1267 | 0.4646          | 0.1809 | 0.0587      | 0.0716           | 0.0505    |
+| 0.347         | 8.0   | 1448 | 0.4682          | 0.1820 | 0.0581      | 0.0720           | 0.0519    |
+| 0.3463        | 9.0   | 1629 | 0.4684          | 0.1827 | 0.0586      | 0.0718           | 0.0523    |
+| 0.3299        | 10.0  | 1810 | 0.4666          | 0.1827 | 0.0590      | 0.0715           | 0.0522    |
+
+
+### Framework versions
+
+- Transformers 4.40.1
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1

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