Model save

README.md

@@ -1,20 +1,15 @@
 ---
 library_name: transformers
-language:
-- jv
 license: apache-2.0
 base_model: openai/whisper-tiny
 tags:
-- whisper
-- javanese
-- asr
 - generated_from_trainer
 datasets:
 - jv_id_asr_split
 metrics:
 - wer
 model-index:
-- name: Whisper Tiny Java
+- name: whisper-tiny-javanese-openslr-v2
   results:
   - task:
       name: Automatic Speech Recognition
@@ -28,18 +23,18 @@ model-index:
     metrics:
     - name: Wer
       type: wer
-      value: 0.4824482518630893
+      value: 0.6471586421539112
 ---
 
 <!-- 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 Tiny Java
+# whisper-tiny-javanese-openslr-v2
 
 This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the jv_id_asr_split dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.5638
-- Wer: 0.4824
+- Loss: 0.2792
+- Wer: 0.6472
 
 ## Model description
 
@@ -58,7 +53,7 @@ More information needed
 ### Training hyperparameters
 
 The following hyperparameters were used during training:
-- learning_rate: 1e-05
+- learning_rate: 2e-05
 - train_batch_size: 64
 - eval_batch_size: 16
 - seed: 42
@@ -67,23 +62,23 @@ The following hyperparameters were used during training:
 - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 5
+- training_steps: 2500
 - mixed_precision_training: Native AMP
 
 ### Training results
 
 | Training Loss | Epoch  | Step | Validation Loss | Wer    |
 |:-------------:|:------:|:----:|:---------------:|:------:|
-| 0.6676        | 0.8643 | 500  | 0.5638          | 0.4824 |
-| 0.4792        | 1.7277 | 1000 | 0.4284          | 0.5330 |
-| 0.3988        | 2.5912 | 1500 | 0.3772          | 0.5687 |
-| 0.3565        | 3.4546 | 2000 | 0.3528          | 0.6204 |
-| 0.3386        | 4.3181 | 2500 | 0.3406          | 0.6603 |
+| 0.528         | 0.8643 | 500  | 0.4467          | 0.4770 |
+| 0.3702        | 1.7277 | 1000 | 0.3424          | 0.5528 |
+| 0.2988        | 2.5946 | 1500 | 0.3031          | 0.5552 |
+| 0.2607        | 3.4581 | 2000 | 0.2859          | 0.6485 |
+| 0.2481        | 4.3215 | 2500 | 0.2792          | 0.6472 |
 
 
 ### Framework versions
 
 - Transformers 4.50.0.dev0
 - Pytorch 2.6.0+cu126
-- Datasets 3.3.2
-- Tokenizers 0.21.0
+- Datasets 3.4.0
+- Tokenizers 0.21.1