End of training

README.md

@@ -22,12 +22,12 @@ should probably proofread and complete it, then remove this comment. -->
 
 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: 0.4284
-- Model Preparation Time: 0.0095
-- Der: 0.1417
-- False Alarm: 0.0235
-- Missed Detection: 0.0281
-- Confusion: 0.0901
+- Loss: 0.4367
+- Model Preparation Time: 0.0045
+- Der: 0.1440
+- False Alarm: 0.0230
+- Missed Detection: 0.0280
+- Confusion: 0.0930
 
 ## Model description
 
@@ -50,7 +50,7 @@ The following hyperparameters were used during training:
 - train_batch_size: 32
 - eval_batch_size: 32
 - seed: 42
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: cosine
 - num_epochs: 5
 
@@ -58,16 +58,16 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Model Preparation Time | Der    | False Alarm | Missed Detection | Confusion |
 |:-------------:|:-----:|:----:|:---------------:|:----------------------:|:------:|:-----------:|:----------------:|:---------:|
-| 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    |
+| 0.4598        | 1.0   | 194  | 0.4815          | 0.0045                 | 0.1608 | 0.0231      | 0.0340           | 0.1036    |
+| 0.3926        | 2.0   | 388  | 0.4519          | 0.0045                 | 0.1545 | 0.0225      | 0.0312           | 0.1008    |
+| 0.3602        | 3.0   | 582  | 0.4442          | 0.0045                 | 0.1476 | 0.0232      | 0.0288           | 0.0956    |
+| 0.3611        | 4.0   | 776  | 0.4388          | 0.0045                 | 0.1443 | 0.0228      | 0.0281           | 0.0934    |
+| 0.3399        | 5.0   | 970  | 0.4367          | 0.0045                 | 0.1440 | 0.0230      | 0.0280           | 0.0930    |
 
 
 ### Framework versions
 
-- Transformers 4.44.2
-- Pytorch 2.5.0+cu121
-- Datasets 3.1.0
-- Tokenizers 0.19.1
+- Transformers 4.47.1
+- Pytorch 2.5.1+cu121
+- Datasets 3.2.0
+- Tokenizers 0.21.0

runs/Jan03_10-57-52_52d3b1bf08f6/events.out.tfevents.1735901884.52d3b1bf08f6.308.0

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+size 16362