End of training

README.md

@@ -11,7 +11,7 @@ datasets:
 metrics:
 - wer
 model-index:
-- name: Whisper Medium - Kiran Pantha
+- name: Whisper Base - Kiran Pantha
   results:
   - task:
       name: Automatic Speech Recognition
@@ -25,18 +25,18 @@ model-index:
     metrics:
     - name: Wer
       type: wer
-      value: 43.58105012370567
+      value: 43.282127708357216
 ---
 
 <!-- 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 Medium - Kiran Pantha
+# Whisper Base - Kiran Pantha
 
 This model is a fine-tuned version of [openai/whisper-base](https://huggingface.co/openai/whisper-base) on the OpenSLR54 dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.2096
-- Wer: 43.5811
+- Loss: 0.2056
+- Wer: 43.2821
 
 ## Model description
 
@@ -69,16 +69,16 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch  | Step | Validation Loss | Wer     |
 |:-------------:|:------:|:----:|:---------------:|:-------:|
-| 0.5243        | 0.1200 | 500  | 0.4983          | 77.1832 |
-| 0.3685        | 0.2399 | 1000 | 0.3600          | 64.9684 |
-| 0.3007        | 0.3599 | 1500 | 0.3094          | 58.0592 |
-| 0.2704        | 0.4798 | 2000 | 0.2785          | 54.5038 |
-| 0.2529        | 0.5998 | 2500 | 0.2560          | 50.7560 |
-| 0.2479        | 0.7198 | 3000 | 0.2407          | 48.4193 |
-| 0.2349        | 0.8397 | 3500 | 0.2262          | 46.3850 |
-| 0.211         | 0.9597 | 4000 | 0.2170          | 45.2305 |
-| 0.1707        | 1.0797 | 4500 | 0.2132          | 44.6990 |
-| 0.1506        | 1.1996 | 5000 | 0.2096          | 43.5811 |
+| 0.5029        | 0.0750 | 500  | 0.4922          | 77.0205 |
+| 0.351         | 0.1499 | 1000 | 0.3561          | 65.6941 |
+| 0.3034        | 0.2249 | 1500 | 0.2988          | 57.0618 |
+| 0.2689        | 0.2999 | 2000 | 0.2714          | 53.2844 |
+| 0.2584        | 0.3749 | 2500 | 0.2537          | 50.8369 |
+| 0.2325        | 0.4498 | 3000 | 0.2393          | 48.0282 |
+| 0.2238        | 0.5248 | 3500 | 0.2271          | 46.5723 |
+| 0.2149        | 0.5998 | 4000 | 0.2149          | 44.4056 |
+| 0.2038        | 0.6748 | 4500 | 0.2091          | 43.6834 |
+| 0.2026        | 0.7497 | 5000 | 0.2056          | 43.2821 |
 
 
 ### Framework versions