Update README.md

README.md

@@ -23,6 +23,9 @@ model-index:
     - name: Wer
       type: wer
       value: 55.432891743610334
+language:
+- th
+pipeline_tag: automatic-speech-recognition
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -31,9 +34,6 @@ should probably proofread and complete it, then remove this comment. -->
 # Whisper-small-thai
 
 This model is a fine-tuned version of [biodatlab/whisper-th-small-combined](https://huggingface.co/biodatlab/whisper-th-small-combined) on the common_voice_17_0 dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.1073
-- Wer: 55.4329
 
 ## Model description
 
@@ -62,15 +62,7 @@ The following hyperparameters were used during training:
 - training_steps: 5000
 - mixed_precision_training: Native AMP
 
-### Training results
 
-| Training Loss | Epoch  | Step | Validation Loss | Wer     |
-|:-------------:|:------:|:----:|:---------------:|:-------:|
-| 0.3415        | 0.3647 | 1000 | 0.1371          | 65.4958 |
-| 0.1638        | 0.7294 | 2000 | 0.1253          | 60.3238 |
-| 0.1995        | 1.0941 | 3000 | 0.1161          | 57.4736 |
-| 0.213         | 1.4588 | 4000 | 0.1104          | 56.2358 |
-| 0.2041        | 1.8235 | 5000 | 0.1073          | 55.4329 |
 
 
 ### Framework versions
@@ -78,4 +70,4 @@ The following hyperparameters were used during training:
 - Transformers 4.43.3
 - Pytorch 2.3.1+cu121
 - Datasets 2.20.0
-- Tokenizers 0.19.1
+- Tokenizers 0.19.1