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: 73.52543899144528
+library_name: transformers
 ---
 
 <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -37,12 +39,12 @@ 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, SpokenWords dataset.
-It achieves the following results on the evaluation set:
-- Loss: 1.6195
-- Bleu: 26.85
-- Chrf: 44.41
-- Wer: 73.5254
+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 datasets.
+The best model (this version) is at checkpoint 3400, epoch 3.67, and it achieves the following results on the evaluation set:
+- Loss: 1.5752
+- Bleu: 30.77
+- Chrf: 46.43
+- Wer: 64.6556
 
 ## Model description
 
@@ -58,6 +60,11 @@ More information needed
 
 ## Training procedure
 
+### Experiment
+
+- language=English
+- +more steps
+
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
@@ -110,11 +117,11 @@ The following hyperparameters were used during training:
 | 0.032         | 3.56  | 3300 | 29.81 | 46.5  | 1.5823          | 66.7267  |
 | 0.0348        | 3.67  | 3400 | 30.77 | 46.43 | 1.5752          | 64.6556  |
 | 0.0277        | 3.78  | 3500 | 30.3  | 46.02 | 1.5791          | 64.6105  |
-| 0.0364        | 3.88  | 3600 | 1.5895| 29.92 | 45.38           | 65.0608  |
-| 0.0398        | 3.99  | 3700 | 1.6167| 27.79 | 44.59           | 68.2575  |
-| 0.0152        | 4.1   | 3800 | 1.6241| 28.42 | 44.83           | 67.5822  |
-| 0.0201        | 4.21  | 3900 | 1.6243| 29.02 | 45.11           | 67.4921  |
-| 0.0168        | 4.31  | 4000 | 1.6195| 26.85 | 44.41           | 73.5254  |
+| 0.0364        | 3.88  | 3600 | 29.92 | 45.38 | 1.5895          | 65.0608  |
+| 0.0398        | 3.99  | 3700 | 27.79 | 44.59 | 1.6167          | 68.2575  |
+| 0.0152        | 4.1   | 3800 | 28.42 | 44.83 | 1.6241          | 67.5822  |
+| 0.0201        | 4.21  | 3900 | 29.02 | 45.11 | 1.6243          | 67.4921  |
+| 0.0168        | 4.31  | 4000 | 26.85 | 44.41 | 1.6195          | 73.5254  |
 
 
 ### Framework versions
@@ -122,4 +129,4 @@ The following hyperparameters were used during training:
 - Transformers 4.39.3
 - Pytorch 2.2.1+cu121
 - Datasets 2.18.0
-- Tokenizers 0.15.2
+- Tokenizers 0.15.2