Update README.md

README.md

@@ -1,88 +1,88 @@
----
-language:
-- en
-license: apache-2.0
-base_model: openai/whisper-small
-tags:
-- generated_from_trainer
-datasets:
-- mozilla-foundation/common_voice_11_0
-metrics:
-- wer
-model-index:
-- name: Whisper Small Refined - Seagate Lim
-  results:
-  - task:
-      name: Automatic Speech Recognition
-      type: automatic-speech-recognition
-    dataset:
-      name: Common Voice 11.0
-      type: mozilla-foundation/common_voice_11_0
-      args: 'config: en, split: test'
-    metrics:
-    - name: Wer
-      type: wer
-      value: 15.384615384615385
----
-
-<!-- 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 Small Refined - Seagate Lim
-
-This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.8921
-- Wer: 15.3846
-
-## 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: 5e-08
-- train_batch_size: 16
-- eval_batch_size: 8
-- seed: 42
-- gradient_accumulation_steps: 2
-- total_train_batch_size: 32
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
-- lr_scheduler_warmup_steps: 250
-- training_steps: 4000
-- mixed_precision_training: Native AMP
-
-### Training results
-
-| Training Loss | Epoch  | Step | Validation Loss | Wer     |
-|:-------------:|:------:|:----:|:---------------:|:-------:|
-| 0.0045        | 400.0  | 400  | 0.9209          | 30.7692 |
-| 0.0008        | 800.0  | 800  | 0.8990          | 15.3846 |
-| 0.0003        | 1200.0 | 1200 | 0.8957          | 15.3846 |
-| 0.0002        | 1600.0 | 1600 | 0.8931          | 15.3846 |
-| 0.0001        | 2000.0 | 2000 | 0.8927          | 15.3846 |
-| 0.0001        | 2400.0 | 2400 | 0.8927          | 15.3846 |
-| 0.0001        | 2800.0 | 2800 | 0.8919          | 15.3846 |
-| 0.0001        | 3200.0 | 3200 | 0.8912          | 15.3846 |
-| 0.0001        | 3600.0 | 3600 | 0.8918          | 15.3846 |
-| 0.0001        | 4000.0 | 4000 | 0.8921          | 15.3846 |
-
-
-### Framework versions
-
-- Transformers 4.42.4
-- Pytorch 2.3.0
-- Datasets 2.19.1
-- Tokenizers 0.19.1
+---
+language:
+- en
+license: apache-2.0
+base_model: openai/whisper-small
+tags:
+- generated_from_trainer
+datasets:
+- mozilla-foundation/common_voice_11_0
+metrics:
+- wer
+model-index:
+- name: Whisper Small Refined
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: Common Voice 11.0
+      type: mozilla-foundation/common_voice_11_0
+      args: 'config: en, split: test'
+    metrics:
+    - name: Wer
+      type: wer
+      value: 15.384615384615385
+---
+
+<!-- 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 Small Refined - Seagate Lim
+
+This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 11.0 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8921
+- Wer: 15.3846
+
+## 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: 5e-08
+- train_batch_size: 16
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 250
+- training_steps: 4000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Wer     |
+|:-------------:|:------:|:----:|:---------------:|:-------:|
+| 0.0045        | 400.0  | 400  | 0.9209          | 30.7692 |
+| 0.0008        | 800.0  | 800  | 0.8990          | 15.3846 |
+| 0.0003        | 1200.0 | 1200 | 0.8957          | 15.3846 |
+| 0.0002        | 1600.0 | 1600 | 0.8931          | 15.3846 |
+| 0.0001        | 2000.0 | 2000 | 0.8927          | 15.3846 |
+| 0.0001        | 2400.0 | 2400 | 0.8927          | 15.3846 |
+| 0.0001        | 2800.0 | 2800 | 0.8919          | 15.3846 |
+| 0.0001        | 3200.0 | 3200 | 0.8912          | 15.3846 |
+| 0.0001        | 3600.0 | 3600 | 0.8918          | 15.3846 |
+| 0.0001        | 4000.0 | 4000 | 0.8921          | 15.3846 |
+
+
+### Framework versions
+
+- Transformers 4.42.4
+- Pytorch 2.3.0
+- Datasets 2.19.1
+- Tokenizers 0.19.1