End of training

README.md

@@ -6,19 +6,19 @@ tags:
 metrics:
 - wer
 model-index:
-- name: Whisper-opus
+- name: opus-base
   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. -->
 
-# Whisper-opus
+# opus-base
 
 This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.0364
-- Wer: 26.1302
+- Loss: 0.0273
+- Wer: 22.7055
 
 ## Model description
 
@@ -37,9 +37,9 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 2e-05
-- train_batch_size: 24
-- eval_batch_size: 8
+- learning_rate: 1e-05
+- train_batch_size: 16
+- eval_batch_size: 2
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
@@ -51,10 +51,8 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch  | Step | Validation Loss | Wer     |
 |:-------------:|:------:|:----:|:---------------:|:-------:|
-| 0.5133        | 0.3671 | 500  | 0.0835          | 50.8073 |
-| 0.0607        | 0.7342 | 1000 | 0.0469          | 32.2390 |
-| 0.0431        | 1.1013 | 1500 | 0.0398          | 27.9064 |
-| 0.0339        | 1.4684 | 2000 | 0.0364          | 26.1302 |
+| 0.0361        | 0.5435 | 1000 | 0.0311          | 25.5805 |
+| 0.0324        | 1.0870 | 2000 | 0.0273          | 22.7055 |
 
 
 ### Framework versions