End of training

README.md

@@ -9,35 +9,25 @@ tags:
 datasets:
 - mozilla-foundation/common_voice_16_1
 - google/fleurs
-metrics:
-- wer
 model-index:
-- name: Whisper Large MN - Ankhbayasgalan Davaadorj
-  results:
-  - task:
-      name: Automatic Speech Recognition
-      type: automatic-speech-recognition
-    dataset:
-      name: Common Voice 16.1 & FLEURS
-      type: mozilla-foundation/common_voice_16_1
-      config: mn
-      split: None
-      args: 'config: mn, split: test+validation'
-    metrics:
-    - name: Wer
-      type: wer
-      value: 30.806886309883946
+- name: Whisper Large V2 MN - Ankhbayasgalan Davaadorj
+  results: []
 ---
 
 <!-- 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 Large MN - Ankhbayasgalan Davaadorj
+# Whisper Large V2 MN - Ankhbayasgalan Davaadorj
 
 This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the Common Voice 16.1 & FLEURS dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.6355
-- Wer: 30.8069
+- eval_loss: 0.2431
+- eval_wer: 19.6462
+- eval_runtime: 212.4702
+- eval_samples_per_second: 0.48
+- eval_steps_per_second: 0.122
+- epoch: 10.99
+- step: 1000
 
 ## Model description
 
@@ -57,44 +47,18 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 1e-05
-- train_batch_size: 16
-- eval_batch_size: 8
+- train_batch_size: 8
+- eval_batch_size: 4
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
 - lr_scheduler_type: linear
 - lr_scheduler_warmup_steps: 500
-- training_steps: 20000
+- training_steps: 2000
 - mixed_precision_training: Native AMP
 
-### Training results
-
-| Training Loss | Epoch  | Step  | Validation Loss | Wer     |
-|:-------------:|:------:|:-----:|:---------------:|:-------:|
-| 0.045         | 5.99   | 1000  | 0.4108          | 37.5062 |
-| 0.0081        | 11.98  | 2000  | 0.4551          | 34.9101 |
-| 0.0072        | 17.96  | 3000  | 0.4533          | 34.0080 |
-| 0.0036        | 23.95  | 4000  | 0.4884          | 33.9475 |
-| 0.0022        | 29.94  | 5000  | 0.4928          | 32.8365 |
-| 0.0029        | 35.93  | 6000  | 0.4907          | 32.9740 |
-| 0.0035        | 41.92  | 7000  | 0.4889          | 32.9245 |
-| 0.0005        | 47.9   | 8000  | 0.5133          | 31.7034 |
-| 0.0017        | 53.89  | 9000  | 0.5086          | 32.4900 |
-| 0.0005        | 59.88  | 10000 | 0.5206          | 31.5274 |
-| 0.001         | 65.87  | 11000 | 0.5128          | 31.8189 |
-| 0.0018        | 71.86  | 12000 | 0.5344          | 32.5560 |
-| 0.0           | 77.84  | 13000 | 0.5471          | 31.2414 |
-| 0.0           | 83.83  | 14000 | 0.5790          | 31.1314 |
-| 0.0           | 89.82  | 15000 | 0.5948          | 30.9609 |
-| 0.0           | 95.81  | 16000 | 0.6069          | 30.9334 |
-| 0.0           | 101.8  | 17000 | 0.6172          | 30.7849 |
-| 0.0           | 107.78 | 18000 | 0.6259          | 30.7189 |
-| 0.0           | 113.77 | 19000 | 0.6326          | 30.7189 |
-| 0.0           | 119.76 | 20000 | 0.6355          | 30.8069 |
-
-
 ### Framework versions
 
 - Transformers 4.38.0.dev0
 - Pytorch 2.2.0+cu121
-- Datasets 2.17.0
+- Datasets 2.17.1
 - Tokenizers 0.15.2

generation_config.json

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