Update README.md

README.md

@@ -1,82 +1,84 @@
----
-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-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: 31.434636476207324
----
-
-<!-- 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-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: 0.5505
-- Wer: 31.4346
-
-## 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: 4000
-- mixed_precision_training: Native AMP
-
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Wer     |
-|:-------------:|:-----:|:----:|:---------------:|:-------:|
-| 0.4824        | 0.16  | 1000 | 0.6305          | 35.5019 |
-| 0.4284        | 0.32  | 2000 | 0.5855          | 33.3615 |
-| 0.4152        | 0.48  | 3000 | 0.5610          | 32.1068 |
-| 0.4387        | 0.64  | 4000 | 0.5505          | 31.4346 |
-
-
-### 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-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: 31.434636476207324
+---
+
+<!-- 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-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: 0.5505
+- Wer: 31.4346
+
+This model is part of my school project, it uses shuffled 100k rows of train dataset since the computation power is limited
+
+## 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: 4000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer     |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|
+| 0.4824        | 0.16  | 1000 | 0.6305          | 35.5019 |
+| 0.4284        | 0.32  | 2000 | 0.5855          | 33.3615 |
+| 0.4152        | 0.48  | 3000 | 0.5610          | 32.1068 |
+| 0.4387        | 0.64  | 4000 | 0.5505          | 31.4346 |
+
+
+### Framework versions
+
+- Transformers 4.40.2
+- Pytorch 2.3.0
+- Datasets 2.19.1
+- Tokenizers 0.19.1