Update README.md

README.md

@@ -6,7 +6,7 @@ datasets:
 metrics:
 - wer
 model-index:
-- name: afrispeech_large_h100_no_puncs_last
+- name: afripspeech_data_aug
   results:
   - task:
       name: Automatic Speech Recognition
@@ -20,18 +20,16 @@ model-index:
     metrics:
     - name: Wer
       type: wer
-      value: 6.152856683460177
+      value: 6.008
 ---
 
 <!-- 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. -->
 
-# afrispeech_large_h100_no_puncs_last
+# afripspeech_data_aug
+
+This model is a fine-tuned version of [afrispeech_large_A100](https://huggingface.co/Seyfelislem/afrispeech_large_A100) on the afrispeech-200 dataset.
 
-This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the afrispeech-200 dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.1213
-- Wer: 6.1529
 
 ## Model description
 
@@ -64,19 +62,7 @@ The following hyperparameters were used during training:
 
 ### Training results
 
-| Training Loss | Epoch | Step | Validation Loss | Wer    |
-|:-------------:|:-----:|:----:|:---------------:|:------:|
-| 0.1578        | 0.1   | 200  | 0.1283          | 5.8313 |
-| 0.1253        | 0.2   | 400  | 0.1475          | 6.8282 |
-| 0.236         | 0.3   | 600  | 0.1505          | 7.2033 |
-| 0.1628        | 0.4   | 800  | 0.1398          | 8.2217 |
-| 0.1213        | 1.05  | 1000 | 0.1316          | 6.1743 |
-| 0.0569        | 1.15  | 1200 | 0.1417          | 6.7960 |
-| 0.0598        | 1.25  | 1400 | 0.1445          | 7.0104 |
-| 0.1262        | 1.35  | 1600 | 0.1269          | 6.4101 |
-| 0.0462        | 2.0   | 1800 | 0.1186          | 5.9706 |
-| 0.0487        | 2.1   | 2000 | 0.1213          | 6.1529 |
-
+https://huggingface.co/Seyfelislem/afrispeech_large_A100/tensorboard
 
 ### Framework versions