End of training

README.md

@@ -1,8 +1,6 @@
 ---
-language:
-- jpn
-license: apache-2.0
-base_model: openai/whisper-small
+license: mit
+base_model: pyannote/segmentation-3.0
 tags:
 - speaker-diarization
 - speaker-segmentation
@@ -19,13 +17,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # speaker-segmentation-fine-tuned-callhome-jpn
 
-This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the diarizers-community/callhome dataset.
+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.
 It achieves the following results on the evaluation set:
-- Loss: 0.7580
-- Der: 0.2252
-- False Alarm: 0.0481
-- Missed Detection: 0.1332
-- Confusion: 0.0438
+- Loss: 0.5146
+- Der: 0.1869
+- False Alarm: 0.0933
+- Missed Detection: 0.0709
+- Confusion: 0.0227
 
 ## Model description
 
@@ -50,22 +48,22 @@ 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
+- num_epochs: 5.0
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Der    | False Alarm | Missed Detection | Confusion |
 |:-------------:|:-----:|:----:|:---------------:|:------:|:-----------:|:----------------:|:---------:|
-| 0.58          | 1.0   | 328  | 0.7581          | 0.2347 | 0.0540      | 0.1313           | 0.0494    |
-| 0.5265        | 2.0   | 656  | 0.7556          | 0.2270 | 0.0473      | 0.1369           | 0.0428    |
-| 0.5388        | 3.0   | 984  | 0.7731          | 0.2295 | 0.0471      | 0.1391           | 0.0434    |
-| 0.4991        | 4.0   | 1312 | 0.7583          | 0.2241 | 0.0483      | 0.1324           | 0.0434    |
-| 0.526         | 5.0   | 1640 | 0.7580          | 0.2252 | 0.0481      | 0.1332           | 0.0438    |
+| 0.6043        | 1.0   | 340  | 0.5075          | 0.1789 | 0.0682      | 0.0789           | 0.0318    |
+| 0.5766        | 2.0   | 680  | 0.5207          | 0.1951 | 0.1012      | 0.0708           | 0.0230    |
+| 0.5345        | 3.0   | 1020 | 0.5011          | 0.1798 | 0.0852      | 0.0716           | 0.0231    |
+| 0.518         | 4.0   | 1360 | 0.5344          | 0.1934 | 0.1009      | 0.0700           | 0.0225    |
+| 0.5147        | 5.0   | 1700 | 0.5146          | 0.1869 | 0.0933      | 0.0709           | 0.0227    |
 
 
 ### Framework versions
 
 - Transformers 4.40.0
-- Pytorch 2.2.1+cu121
-- Datasets 2.19.0
+- Pytorch 2.2.2+cu121
+- Datasets 2.18.0
 - Tokenizers 0.19.1

model.safetensors

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:fb75adfe1650c554638e3fc497d1aae1769572b2d642a8af5277107f06ca60c0
+oid sha256:0a0c2ffb5faa5aff4a62c35eb0db55858affdfbdd3d1abc8034ce5c8e1a2f1c5
 size 5899124