End of training

README.md

@@ -21,11 +21,15 @@ should probably proofread and complete it, then remove this comment. -->
 
 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: 0.5893
-- Der: 0.1935
-- False Alarm: 0.0760
-- Missed Detection: 0.0713
-- Confusion: 0.0461
+- eval_loss: 0.8263
+- eval_der: 0.2702
+- eval_false_alarm: 0.0280
+- eval_missed_detection: 0.1843
+- eval_confusion: 0.0579
+- eval_runtime: 80.4369
+- eval_samples_per_second: 8.64
+- eval_steps_per_second: 0.274
+- step: 0
 
 ## Model description
 
@@ -52,20 +56,9 @@ The following hyperparameters were used during training:
 - lr_scheduler_type: cosine
 - num_epochs: 5
 
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Der    | False Alarm | Missed Detection | Confusion |
-|:-------------:|:-----:|:----:|:---------------:|:------:|:-----------:|:----------------:|:---------:|
-| 0.5956        | 1.0   | 336  | 0.6028          | 0.2004 | 0.0637      | 0.0824           | 0.0543    |
-| 0.5696        | 2.0   | 672  | 0.6137          | 0.2001 | 0.0760      | 0.0741           | 0.0500    |
-| 0.5334        | 3.0   | 1008 | 0.5886          | 0.1941 | 0.0787      | 0.0701           | 0.0453    |
-| 0.5168        | 4.0   | 1344 | 0.5914          | 0.1933 | 0.0745      | 0.0723           | 0.0465    |
-| 0.5174        | 5.0   | 1680 | 0.5893          | 0.1935 | 0.0760      | 0.0713           | 0.0461    |
-
-
 ### Framework versions
 
 - Transformers 4.40.0
 - Pytorch 2.2.1+cu121
-- Datasets 2.18.0
+- Datasets 2.19.0
 - Tokenizers 0.19.1

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training_args.bin

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