End of training

README.md

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+---
+language:
+- eng
+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-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-fine-tuned-callhome-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: 0.4597
+- Der: 0.1816
+- False Alarm: 0.0595
+- Missed Detection: 0.0708
+- Confusion: 0.0513
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:-----------:|:----------------:|:---------:|
+| 0.3871        | 1.0   | 362  | 0.4735          | 0.1913 | 0.0608      | 0.0744           | 0.0561    |
+| 0.4079        | 2.0   | 724  | 0.4605          | 0.1850 | 0.0626      | 0.0700           | 0.0524    |
+| 0.3871        | 3.0   | 1086 | 0.4603          | 0.1816 | 0.0581      | 0.0726           | 0.0509    |
+| 0.3642        | 4.0   | 1448 | 0.4624          | 0.1817 | 0.0575      | 0.0723           | 0.0519    |
+| 0.3421        | 5.0   | 1810 | 0.4597          | 0.1816 | 0.0595      | 0.0708           | 0.0513    |
+
+
+### Framework versions
+
+- Transformers 4.40.0
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.0
+- Tokenizers 0.19.1