Training in progress, epoch 1

README.md

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+---
+library_name: transformers
+license: mit
+base_model: pyannote/segmentation-3.0
+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 [pyannote/segmentation-3.0](https://huggingface.co/pyannote/segmentation-3.0) on the diarizers-community/callhome eng dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4759
+- Der: 0.1904
+- False Alarm: 0.0618
+- Missed Detection: 0.0722
+- Confusion: 0.0565
+
+## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
+- lr_scheduler_type: cosine
+- num_epochs: 5.0
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Der    | False Alarm | Missed Detection | Confusion |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:-----------:|:----------------:|:---------:|
+| 0.4503        | 1.0   | 181  | 0.4741          | 0.1951 | 0.0605      | 0.0754           | 0.0592    |
+| 0.4189        | 2.0   | 362  | 0.4848          | 0.1943 | 0.0654      | 0.0741           | 0.0548    |
+| 0.4007        | 3.0   | 543  | 0.4817          | 0.1939 | 0.0651      | 0.0713           | 0.0575    |
+| 0.3938        | 4.0   | 724  | 0.4778          | 0.1909 | 0.0623      | 0.0722           | 0.0564    |
+| 0.3949        | 5.0   | 905  | 0.4759          | 0.1904 | 0.0618      | 0.0722           | 0.0565    |
+
+
+### Framework versions
+
+- Transformers 4.47.1
+- Pytorch 2.3.0+cu118
+- Datasets 3.2.0
+- Tokenizers 0.21.0

config.json

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+{
+  "architectures": [
+    "SegmentationModel"
+  ],
+  "chunk_duration": 10.0,
+  "max_speakers_per_chunk": 3,
+  "max_speakers_per_frame": 2,
+  "min_duration": null,
+  "model_type": "pyannet",
+  "sample_rate": 16000,
+  "torch_dtype": "float32",
+  "transformers_version": "4.47.1",
+  "warm_up": [
+    0.0,
+    0.0
+  ],
+  "weigh_by_cardinality": false
+}

model.safetensors

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runs/Dec28_20-29-08_DESKTOP-47FFOK2/events.out.tfevents.1735398460.DESKTOP-47FFOK2.2076.0

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runs/Dec30_12-33-50_DESKTOP-47FFOK2/events.out.tfevents.1735542467.DESKTOP-47FFOK2.1576.0

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training_args.bin

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