Update README.md

README.md

@@ -6,7 +6,8 @@ tags:
 - whisper-event
 - generated_from_trainer
 datasets:
-- mozilla-foundation/common_voice_11_0
+- mozilla-foundation/common_voice_13_0
+- google/fleurs
 metrics:
 - wer
 model-index:
@@ -25,6 +26,7 @@ model-index:
     - name: Wer
       type: wer
       value: 8.44
+library_name: transformers
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -32,8 +34,8 @@ should probably proofread and complete it, then remove this comment. -->
 
 # Whisper Medium (Thai): Combined V2
 
-This model is a fine-tuned version of [biodatlab/whisper-medium-th-1000iter](https://huggingface.co/biodatlab/whisper-medium-th-1000iter) on the mozilla-foundation/common_voice_11_0 th dataset.
-It achieves the following results on the evaluation set:
+This model is a fine-tuned, augmented versions of [biodatlab/whisper-medium-th-1000iter](https://huggingface.co/biodatlab/whisper-medium-th-1000iter) on the mozilla-foundation/common_voice_13_0 th, google/fleurs, and curated datasets.
+It achieves the following results (NOT-UP-TO-DATE) on the common-voice-11 evaluation set:
 - Loss: 0.1475
 - WER: 13.03 (without Tokenizer)
 - WER: 8.44 (with Deepcut Tokenizer)
@@ -45,7 +47,7 @@ Use the model with huggingface's `transformers` as follows:
 ```py
 from transformers import pipeline
 
-MODEL_NAME = "biodatlab/whisper-medium-th-combined-v2"  # specify the model name
+MODEL_NAME = "biodatlab/whisper-medium-th-combined"  # specify the model name
 lang = "th"  # change to Thai langauge
 
 device = 0 if torch.cuda.is_available() else "cpu"
@@ -96,10 +98,10 @@ The following hyperparameters were used during training:
 
 ### Framework versions
 
-- Transformers 4.26.0.dev0
-- Pytorch 1.13.0
-- Datasets 2.7.1
-- Tokenizers 0.13.2
+- Transformers 4.31.0.dev0
+- Pytorch 2.1.0
+- Datasets 2.13.1
+- Tokenizers 0.13.3
 
 ## Citation