Update README.md

README.md

@@ -14,6 +14,7 @@ datasets:
 metrics:
 - bleu
 - wer
+- chrf
 model-index:
 - name: Whisper Small GA-EN Speech Translation
   results:
@@ -30,6 +31,7 @@ model-index:
     - name: Wer
       type: wer
       value: 72.0396217919856
+library_name: transformers
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -37,12 +39,14 @@ should probably proofread and complete it, then remove this comment. -->
 
 # Whisper Small GA-EN Speech Translation
 
-This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the IWSLT-2023, FLEURS, BiteSize, and SpokenWords dataset.
-It achieves the following results on the evaluation set:
-- Loss: 1.7786
-- Bleu: 27.66
-- Chrf: 43.04
-- Wer: 72.0396
+This model is a fine-tuned version of openai/whisper-small on the IWSLT-2023, FLEURS, BiteSize, and SpokenWords datasets.
+The best model checkpoint (this version) based on ChrF is at step 2100, epoch 4.5259, and
+it achieves the following results on the evaluation set:
+- Loss: 1.7200
+- Bleu: 29.83
+- Chrf: 44.87
+- Wer: 64.8807
+
 
 ## Model description
 
@@ -111,4 +115,4 @@ The following hyperparameters were used during training:
 - Transformers 4.40.2
 - Pytorch 2.2.0+cu121
 - Datasets 2.19.1
-- Tokenizers 0.19.1
+- Tokenizers 0.19.1