Update README.md

README.md

@@ -1,86 +1,89 @@
----
-language:
-- de
-license: apache-2.0
-base_model: openai/whisper-tiny
-tags:
-- generated_from_trainer
-datasets:
-- mozilla-foundation/common_voice_11_0
-metrics:
-- wer
-model-index:
-- name: whisper-tiny-german-V2-HanNeurAI
-  results:
-  - task:
-      name: Automatic Speech Recognition
-      type: automatic-speech-recognition
-    dataset:
-      name: Common Voice 11.0
-      type: mozilla-foundation/common_voice_11_0
-      config: de
-      split: test
-      args: 'config: de, split: test'
-    metrics:
-    - name: Wer
-      type: wer
-      value: 32.33273006844562
----
-
-<!-- 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-german-V2-HanNeurAI
-
-This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 11.0 dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.5818
-- Wer: 32.3327
-
-## Model description
-
-More information needed
-
-## Intended uses & limitations
-
-More information needed
-
-## Training and evaluation data
-
-More information needed
-
-## Training procedure
-
-### Training hyperparameters
-
-The following hyperparameters were used during training:
-- learning_rate: 1e-05
-- train_batch_size: 16
-- eval_batch_size: 8
-- 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: 8000
-- mixed_precision_training: Native AMP
-
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Wer     |
-|:-------------:|:-----:|:----:|:---------------:|:-------:|
-| 0.2054        | 0.08  | 1000 | 0.7062          | 39.0698 |
-| 0.1861        | 0.16  | 2000 | 0.6687          | 36.4857 |
-| 0.1677        | 0.24  | 3000 | 0.6393          | 35.6849 |
-| 0.2019        | 0.32  | 4000 | 0.6193          | 34.4385 |
-| 0.1808        | 0.4   | 5000 | 0.6103          | 33.8459 |
-| 0.1697        | 0.48  | 6000 | 0.5956          | 32.8519 |
-| 0.1468        | 0.56  | 7000 | 0.5884          | 32.7029 |
-| 0.1906        | 0.64  | 8000 | 0.5818          | 32.3327 |
-
-
-### Framework versions
-
-- Transformers 4.40.2
-- Pytorch 2.3.0
-- Datasets 2.19.1
-- Tokenizers 0.19.1
+---
+language:
+- de
+license: apache-2.0
+base_model: openai/whisper-tiny
+tags:
+- generated_from_trainer
+datasets:
+- mozilla-foundation/common_voice_11_0
+metrics:
+- wer
+model-index:
+- name: whisper-tiny-german-V2-HanNeurAI
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Common Voice 11.0 German shuffled 200k rows
+      type: mozilla-foundation/common_voice_11_0
+      config: de
+      split: test
+      args: 'config: de, split: test'
+    metrics:
+    - name: Wer
+      type: wer
+      value: 32.33273006844562
+---
+
+<!-- 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-german-V2-HanNeurAI
+
+This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co/openai/whisper-tiny) on the Common Voice 11.0 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5818
+- Wer: 32.3327
+
+This fine-tuning model is part of my school project.
+With limitation of my compute, I scale down the dataset from german common voice to shuffled 100k rows
+## Model description
+
+Model Parameter (pipe.model.num_parameters()): 37760640 (37M)
+
+
+## Intended uses & limitations
+
+More information needed
+
+## Training and evaluation data
+
+More information needed
+
+## Training procedure
+
+### Training hyperparameters
+
+The following hyperparameters were used during training:
+- learning_rate: 1e-05
+- train_batch_size: 16
+- eval_batch_size: 8
+- 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: 8000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer     |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|
+| 0.2054        | 0.08  | 1000 | 0.7062          | 39.0698 |
+| 0.1861        | 0.16  | 2000 | 0.6687          | 36.4857 |
+| 0.1677        | 0.24  | 3000 | 0.6393          | 35.6849 |
+| 0.2019        | 0.32  | 4000 | 0.6193          | 34.4385 |
+| 0.1808        | 0.4   | 5000 | 0.6103          | 33.8459 |
+| 0.1697        | 0.48  | 6000 | 0.5956          | 32.8519 |
+| 0.1468        | 0.56  | 7000 | 0.5884          | 32.7029 |
+| 0.1906        | 0.64  | 8000 | 0.5818          | 32.3327 |
+
+
+### Framework versions
+
+- Transformers 4.40.2
+- Pytorch 2.3.0
+- Datasets 2.19.1
+- Tokenizers 0.19.1