End of training

README.md

@@ -0,0 +1,71 @@
+---
+language:
+- eng
+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 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4692
+- Der: 0.1840
+- False Alarm: 0.0616
+- Missed Detection: 0.0711
+- 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 |
+|:-------------:|:-----:|:----:|:---------------:|:------:|:-----------:|:----------------:|:---------:|
+| 0.3907        | 1.0   | 362  | 0.4760          | 0.1920 | 0.0622      | 0.0739           | 0.0559    |
+| 0.4104        | 2.0   | 724  | 0.4737          | 0.1912 | 0.0704      | 0.0688           | 0.0520    |
+| 0.3848        | 3.0   | 1086 | 0.4567          | 0.1809 | 0.0595      | 0.0709           | 0.0504    |
+| 0.3688        | 4.0   | 1448 | 0.4680          | 0.1831 | 0.0581      | 0.0738           | 0.0512    |
+| 0.344         | 5.0   | 1810 | 0.4692          | 0.1840 | 0.0616      | 0.0711           | 0.0513    |
+
+
+### Framework versions
+
+- Transformers 4.40.0
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.0
+- Tokenizers 0.19.1

pytorch_model.bin

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:0ab72734e13717b24e65ac4e38c5a595f3243b031115e4c1b26fd15bfd8ed916
+oid sha256:a3c3e7d38d46f12b104aaf2cf04d443533966bc280d958e7a82ae5b8d016e72c
 size 5904883

runs/Apr25_14-37-11_9816076f8c0c/events.out.tfevents.1714055848.9816076f8c0c.451.0

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:aa447a726b1c151323280609738a37fc596f5e9d19c811535823f46bd2422203
-size 18753
+oid sha256:df58c9410e80e372da04247fa8a1d3f4824b0b328af189e8888700e786ddeee6
+size 22758