update model card README.md

README.md

@@ -4,45 +4,29 @@ language:
 license: apache-2.0
 tags:
 - whisper-event
+- generated_from_trainer
 datasets:
 - mozilla-foundation/common_voice_11_0
-- google/fleurs
-- thennal/IMaSC
-- thennal/ulca_ml
-- thennal/msc
-- thennal/indic_tts_ml
-metrics:
-- wer
 model-index:
-- name: "Whisper Medium Malayalam - Thennal D K"
-  results:
-  - task:
-      name: Automatic Speech Recognition
-      type: automatic-speech-recognition
-    dataset:
-      name: Common Voice 11.0
-      type: mozilla-foundation/common_voice_11_0
-      config: ml
-      split: test
-      args: ml
-    metrics:
-    - name: Wer
-      type: wer
-      value: 42.98850574712644
-    - name: Cer
-      type: cer
-      value: 10.390585878818229
+- name: Whisper Medium Malayalam
+  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 Medium Malayalam - Thennal D K
+# Whisper Medium Malayalam
 
-This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on a combined dataset sourced from IMaSC, 
-SMC, Indic TTS, FLEURS (train set), Common Voice 11 (train + other set), OpenSLR, and ULCA.
-It achieves the following results on the evaluation set (Common Voice 11 test split):
-- Loss: 0.0730
-- WER: 42.9886
-- CER: 10.3906
+This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 11.0 dataset.
+It achieves the following results on the evaluation set:
+- eval_loss: 0.0833
+- eval_wer: 43.6782
+- eval_cer: 9.6895
+- eval_runtime: 437.7464
+- eval_samples_per_second: 0.256
+- eval_steps_per_second: 0.016
+- epoch: 3.59
+- step: 7000
 
 ## Model description
 
@@ -68,7 +52,7 @@ The following hyperparameters were used during training:
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_steps: 500
-- training_steps: 4000
+- training_steps: 8000
 - mixed_precision_training: Native AMP
 
 ### Framework versions