Update README.md

README.md

@@ -1,82 +1,82 @@
----
-library_name: transformers
-license: apache-2.0
-base_model: openai/whisper-medium
-tags:
-- generated_from_trainer
-datasets:
-- fsicoli/cv16-fleurs
-metrics:
-- wer
-model-index:
-- name: whisper-medium-pt-cv16-fleurs2-lr
-  results:
-  - task:
-      name: Automatic Speech Recognition
-      type: automatic-speech-recognition
-    dataset:
-      name: fsicoli/cv16-fleurs default
-      type: fsicoli/cv16-fleurs
-      args: default
-    metrics:
-    - name: Wer
-      type: wer
-      value: 0.103035685451316
----
-
-<!-- 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-medium-pt-cv16-fleurs2-lr
-
-This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the fsicoli/cv16-fleurs default dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.1601
-- Wer: 0.1030
-
-## 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: 6.25e-06
-- train_batch_size: 8
-- eval_batch_size: 8
-- seed: 42
-- gradient_accumulation_steps: 2
-- total_train_batch_size: 16
-- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
-- lr_scheduler_type: linear
-- lr_scheduler_warmup_steps: 5000
-- training_steps: 25000
-- mixed_precision_training: Native AMP
-
-### Training results
-
-| Training Loss | Epoch   | Step  | Validation Loss | Wer    |
-|:-------------:|:-------:|:-----:|:---------------:|:------:|
-| 0.0856        | 2.3343  | 5000  | 0.1601          | 0.1030 |
-| 0.0156        | 4.6685  | 10000 | 0.1831          | 0.1003 |
-| 0.0189        | 7.0028  | 15000 | 0.1996          | 0.0980 |
-| 0.0052        | 9.3371  | 20000 | 0.2079          | 0.0956 |
-| 0.0035        | 11.6713 | 25000 | 0.2088          | 0.0932 |
-
-
-### Framework versions
-
-- Transformers 4.45.0.dev0
-- Pytorch 2.4.1
-- Datasets 2.21.0
-- Tokenizers 0.19.1
+---
+library_name: transformers
+license: apache-2.0
+base_model: openai/whisper-medium
+tags:
+- generated_from_trainer
+datasets:
+- fsicoli/cv16-fleurs
+metrics:
+- wer
+model-index:
+- name: whisper-medium-pt-cv16-fleurs2-lr
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: fsicoli/cv16-fleurs default
+      type: fsicoli/cv16-fleurs
+      args: default
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.0932
+---
+
+<!-- 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-medium-pt-cv16-fleurs2-lr
+
+This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the fsicoli/cv16-fleurs default dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2088
+- Wer: 0.0932
+
+## 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: 6.25e-06
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 2
+- total_train_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 5000
+- training_steps: 25000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch   | Step  | Validation Loss | Wer    |
+|:-------------:|:-------:|:-----:|:---------------:|:------:|
+| 0.0856        | 2.3343  | 5000  | 0.1601          | 0.1030 |
+| 0.0156        | 4.6685  | 10000 | 0.1831          | 0.1003 |
+| 0.0189        | 7.0028  | 15000 | 0.1996          | 0.0980 |
+| 0.0052        | 9.3371  | 20000 | 0.2079          | 0.0956 |
+| 0.0035        | 11.6713 | 25000 | 0.2088          | 0.0932 |
+
+
+### Framework versions
+
+- Transformers 4.45.0.dev0
+- Pytorch 2.4.1
+- Datasets 2.21.0
+- Tokenizers 0.19.1