End of training

README.md

@@ -1,7 +1,7 @@
 ---
 library_name: transformers
 language:
-- jpn
+- hi
 license: mit
 base_model: pyannote/speaker-diarization-3.1
 tags:
@@ -9,25 +9,25 @@ tags:
 - speaker-segmentation
 - generated_from_trainer
 datasets:
-- diarizers-community/callhome
+- Samyak29/synthetic-speaker-diarization-dataset-hindi-large
 model-index:
-- name: speaker-segmentation-fine-tuned-callhome-jpn
+- name: speaker-segmentation-fine-tuned-hindi
   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
+# speaker-segmentation-fine-tuned-hindi
 
-This model is a fine-tuned version of [pyannote/speaker-diarization-3.1](https://huggingface.co/pyannote/speaker-diarization-3.1) on the diarizers-community/callhome dataset.
+This model is a fine-tuned version of [pyannote/speaker-diarization-3.1](https://huggingface.co/pyannote/speaker-diarization-3.1) on the Samyak29/synthetic-speaker-diarization-dataset-hindi-large dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.4370
-- Model Preparation Time: 0.0038
-- Der: 0.1404
-- False Alarm: 0.0234
-- Missed Detection: 0.0272
-- Confusion: 0.0898
+- Loss: 0.4284
+- Model Preparation Time: 0.0095
+- Der: 0.1417
+- False Alarm: 0.0235
+- Missed Detection: 0.0281
+- Confusion: 0.0901
 
 ## Model description
 
@@ -58,11 +58,11 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Der    | False Alarm | Missed Detection | Confusion |
 |:-------------:|:-----:|:----:|:---------------:|:----------------------:|:------:|:-----------:|:----------------:|:---------:|
-| 0.4567        | 1.0   | 194  | 0.4782          | 0.0038                 | 0.1572 | 0.0219      | 0.0351           | 0.1003    |
-| 0.384         | 2.0   | 388  | 0.4576          | 0.0038                 | 0.1483 | 0.0221      | 0.0295           | 0.0968    |
-| 0.3582        | 3.0   | 582  | 0.4375          | 0.0038                 | 0.1402 | 0.0230      | 0.0284           | 0.0888    |
-| 0.357         | 4.0   | 776  | 0.4406          | 0.0038                 | 0.1413 | 0.0229      | 0.0277           | 0.0907    |
-| 0.3406        | 5.0   | 970  | 0.4370          | 0.0038                 | 0.1404 | 0.0234      | 0.0272           | 0.0898    |
+| 0.4708        | 1.0   | 194  | 0.4808          | 0.0095                 | 0.1613 | 0.0255      | 0.0323           | 0.1035    |
+| 0.388         | 2.0   | 388  | 0.4553          | 0.0095                 | 0.1499 | 0.0225      | 0.0314           | 0.0960    |
+| 0.3654        | 3.0   | 582  | 0.4368          | 0.0095                 | 0.1433 | 0.0242      | 0.0278           | 0.0913    |
+| 0.363         | 4.0   | 776  | 0.4296          | 0.0095                 | 0.1410 | 0.0239      | 0.0279           | 0.0893    |
+| 0.3388        | 5.0   | 970  | 0.4284          | 0.0095                 | 0.1417 | 0.0235      | 0.0281           | 0.0901    |
 
 
 ### Framework versions

runs/Nov11_10-53-43_0b8c24355c6d/events.out.tfevents.1731322442.0b8c24355c6d.334.0

@@ -1,3 +1,3 @@
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-size 15317
+oid sha256:4cf447df09914e0277381089d7bd1efd0cb6a5983585b3756d20fbde1baffcf5
+size 16223