End of training

README.md

@@ -1,6 +1,8 @@
 ---
-license: mit
-base_model: pyannote/segmentation-3.0
+language:
+- jpn
+license: apache-2.0
+base_model: openai/whisper-small
 tags:
 - speaker-diarization
 - speaker-segmentation
@@ -17,13 +19,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # speaker-segmentation-fine-tuned-callhome-jpn
 
-This model is a fine-tuned version of [pyannote/segmentation-3.0](https://huggingface.co/pyannote/segmentation-3.0) on the diarizers-community/callhome jpn dataset.
+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: 0.5957
-- Der: 0.1975
-- False Alarm: 0.0777
-- Missed Detection: 0.0713
-- Confusion: 0.0485
+- Loss: 0.7483
+- Der: 0.2246
+- False Alarm: 0.0483
+- Missed Detection: 0.1328
+- Confusion: 0.0435
 
 ## Model description
 
@@ -48,22 +50,22 @@ The following hyperparameters were used during training:
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: cosine
-- num_epochs: 5.0
+- num_epochs: 5
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Der    | False Alarm | Missed Detection | Confusion |
 |:-------------:|:-----:|:----:|:---------------:|:------:|:-----------:|:----------------:|:---------:|
-| 0.5998        | 1.0   | 336  | 0.6155          | 0.2067 | 0.0726      | 0.0792           | 0.0549    |
-| 0.578         | 2.0   | 672  | 0.6258          | 0.2086 | 0.0851      | 0.0691           | 0.0544    |
-| 0.5431        | 3.0   | 1008 | 0.6054          | 0.2023 | 0.0830      | 0.0689           | 0.0505    |
-| 0.5198        | 4.0   | 1344 | 0.5989          | 0.1984 | 0.0762      | 0.0729           | 0.0494    |
-| 0.5211        | 5.0   | 1680 | 0.5957          | 0.1975 | 0.0777      | 0.0713           | 0.0485    |
+| 0.5757        | 1.0   | 328  | 0.7538          | 0.2333 | 0.0470      | 0.1387           | 0.0477    |
+| 0.5269        | 2.0   | 656  | 0.7608          | 0.2275 | 0.0474      | 0.1361           | 0.0439    |
+| 0.5004        | 3.0   | 984  | 0.7516          | 0.2267 | 0.0463      | 0.1369           | 0.0435    |
+| 0.4892        | 4.0   | 1312 | 0.7440          | 0.2241 | 0.0498      | 0.1317           | 0.0426    |
+| 0.5122        | 5.0   | 1640 | 0.7483          | 0.2246 | 0.0483      | 0.1328           | 0.0435    |
 
 
 ### Framework versions
 
 - Transformers 4.40.0
-- Pytorch 2.2.2+cu121
-- Datasets 2.18.0
+- Pytorch 2.2.1+cu121
+- Datasets 2.19.0
 - Tokenizers 0.19.1

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:a2182c1b19d59ed3c329718d47a1155067e4253651fc8ed5168740ff094a0777
+oid sha256:7431f72bcc2fe30a709721d5ea27d79f79e82f1e8efc68d5fc05f8e3a08b0a11
 size 5899124