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-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: 0.5893
+- Der: 0.1935
+- False Alarm: 0.0760
+- Missed Detection: 0.0713
+- Confusion: 0.0461
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:-----------:|:----------------:|:---------:|
+| 0.5956        | 1.0   | 336  | 0.6028          | 0.2004 | 0.0637      | 0.0824           | 0.0543    |
+| 0.5696        | 2.0   | 672  | 0.6137          | 0.2001 | 0.0760      | 0.0741           | 0.0500    |
+| 0.5334        | 3.0   | 1008 | 0.5886          | 0.1941 | 0.0787      | 0.0701           | 0.0453    |
+| 0.5168        | 4.0   | 1344 | 0.5914          | 0.1933 | 0.0745      | 0.0723           | 0.0465    |
+| 0.5174        | 5.0   | 1680 | 0.5893          | 0.1935 | 0.0760      | 0.0713           | 0.0461    |
+
+
+### Framework versions
+
+- Transformers 4.40.0
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.19.1

config.json

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+{
+  "architectures": [
+    "SegmentationModel"
+  ],
+  "chunk_duration": 10,
+  "max_speakers_per_chunk": 3,
+  "max_speakers_per_frame": 2,
+  "min_duration": null,
+  "model_type": "pyannet",
+  "sample_rate": 16000,
+  "torch_dtype": "float32",
+  "transformers_version": "4.40.0",
+  "warm_up": [
+    0.0,
+    0.0
+  ],
+  "weigh_by_cardinality": false
+}

model.safetensors

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+size 5899124

runs/Apr19_08-14-48_de555f671a4e/events.out.tfevents.1713514656.de555f671a4e.1663.0

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training_args.bin

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