End of training

README.md

@@ -22,7 +22,7 @@ model-index:
     metrics:
     - name: Wer
       type: wer
-      value: 0.4040590405904059
+      value: 0.35301353013530135
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,9 +32,9 @@ should probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the PolyAI/minds14 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.7329
-- Wer Ortho: 41.4414
-- Wer: 0.4041
+- Loss: 0.8440
+- Wer Ortho: 34.6847
+- Wer: 0.3530
 
 ## Model description
 
@@ -53,20 +53,29 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 1e-05
-- train_batch_size: 16
-- eval_batch_size: 64
+- learning_rate: 5e-05
+- train_batch_size: 32
+- eval_batch_size: 32
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: constant_with_warmup
-- lr_scheduler_warmup_steps: 500
-- training_steps: 500
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 50
+- training_steps: 1000
 
 ### Training results
 
 | Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer    |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|
-| 0.004         | 17.24 | 500  | 0.7329          | 41.4414   | 0.4041 |
+| 0.0234        | 6.67  | 100  | 0.6639          | 34.2986   | 0.3383 |
+| 0.003         | 13.33 | 200  | 0.7587          | 33.9768   | 0.3401 |
+| 0.0005        | 20.0  | 300  | 0.7870          | 34.2342   | 0.3475 |
+| 0.0003        | 26.67 | 400  | 0.8045          | 35.1351   | 0.3567 |
+| 0.0002        | 33.33 | 500  | 0.8144          | 35.5856   | 0.3610 |
+| 0.0001        | 40.0  | 600  | 0.8262          | 35.5212   | 0.3604 |
+| 0.0001        | 46.67 | 700  | 0.8341          | 35.3282   | 0.3592 |
+| 0.0001        | 53.33 | 800  | 0.8397          | 35.1995   | 0.3579 |
+| 0.0001        | 60.0  | 900  | 0.8426          | 34.7490   | 0.3536 |
+| 0.0001        | 66.67 | 1000 | 0.8440          | 34.6847   | 0.3530 |
 
 
 ### Framework versions