update model card README.md

README.md

@@ -8,7 +8,7 @@ datasets:
 metrics:
 - wer
 model-index:
-- name: whisper-tiny-dv-v2
+- name: whisper-tiny-dv
   results:
   - task:
       name: Automatic Speech Recognition
@@ -22,19 +22,19 @@ model-index:
     metrics:
     - name: Wer
       type: wer
-      value: 55.371900826446286
+      value: 57.438016528925615
 ---
 
 <!-- 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-tiny-dv-v2
+# whisper-tiny-dv
 
 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: 1.0739
-- Wer Ortho: 56.0148
-- Wer: 55.3719
+- Loss: 1.4917
+- Wer Ortho: 58.5441
+- Wer: 57.4380
 
 ## Model description
 
@@ -60,13 +60,22 @@ The following hyperparameters were used during training:
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: constant_with_warmup
 - lr_scheduler_warmup_steps: 50
-- training_steps: 500
+- training_steps: 5000
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer     |
-|:-------------:|:-----:|:----:|:---------------:|:---------:|:-------:|
-| 0.0013        | 17.86 | 500  | 1.0739          | 56.0148   | 55.3719 |
+| Training Loss | Epoch  | Step | Validation Loss | Wer Ortho | Wer     |
+|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|
+| 0.0013        | 17.86  | 500  | 1.0739          | 56.0148   | 55.3719 |
+| 0.0003        | 35.71  | 1000 | 1.1575          | 54.3492   | 53.6009 |
+| 0.0002        | 53.57  | 1500 | 1.2226          | 55.3979   | 54.7226 |
+| 0.0001        | 71.43  | 2000 | 1.2711          | 56.6934   | 55.4900 |
+| 0.0001        | 89.29  | 2500 | 1.3089          | 56.1999   | 55.1948 |
+| 0.0           | 107.14 | 3000 | 1.3487          | 55.4596   | 54.4864 |
+| 0.0           | 125.0  | 3500 | 1.3865          | 56.4466   | 55.5490 |
+| 0.0           | 142.86 | 4000 | 1.4259          | 58.9759   | 57.6741 |
+| 0.0           | 160.71 | 4500 | 1.4563          | 58.2973   | 57.0838 |
+| 0.0           | 178.57 | 5000 | 1.4917          | 58.5441   | 57.4380 |
 
 
 ### Framework versions