Update README.md

README.md

@@ -1,87 +1,87 @@
----
-library_name: transformers
-license: apache-2.0
-base_model: openai/whisper-large-v3
-tags:
-- generated_from_trainer
-datasets:
-- fsicoli/cv19-fleurs
-metrics:
-- wer
-model-index:
-- name: whisper-large-v3-pt-cv19-fleurs
-  results:
-  - task:
-      name: Automatic Speech Recognition
-      type: automatic-speech-recognition
-    dataset:
-      name: fsicoli/cv19-fleurs default
-      type: fsicoli/cv19-fleurs
-      args: default
-    metrics:
-    - name: Wer
-      type: wer
-      value: 0.08493312855954438
----
-
-<!-- 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-v3-pt-cv19-fleurs
-
-This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the fsicoli/cv19-fleurs default dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.1823
-- Wer: 0.0849
-
-## 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: 10000
-- training_steps: 50000
-- mixed_precision_training: Native AMP
-
-### Training results
-
-| Training Loss | Epoch   | Step  | Validation Loss | Wer    |
-|:-------------:|:-------:|:-----:|:---------------:|:------:|
-| 0.0559        | 2.2883  | 5000  | 0.1096          | 0.0730 |
-| 0.0581        | 4.5767  | 10000 | 0.1326          | 0.0829 |
-| 0.0225        | 6.8650  | 15000 | 0.1570          | 0.0849 |
-| 0.0088        | 9.1533  | 20000 | 0.1704          | 0.0840 |
-| 0.0065        | 11.4416 | 25000 | 0.1823          | 0.0849 |
-| 0.006         | 13.7300 | 30000 | 0.1808          | 0.0809 |
-| 0.0055        | 16.0183 | 35000 | 0.1811          | 0.0790 |
-| 0.0031        | 18.3066 | 40000 | 0.1907          | 0.0784 |
-| 0.0011        | 20.5950 | 45000 | 0.1852          | 0.0771 |
-| 0.0003        | 22.8833 | 50000 | 0.1848          | 0.0756 |
-
-
-### 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-large-v3
+tags:
+- generated_from_trainer
+datasets:
+- fsicoli/cv19-fleurs
+metrics:
+- wer
+model-index:
+- name: whisper-large-v3-pt-cv19-fleurs
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: fsicoli/cv19-fleurs default
+      type: fsicoli/cv19-fleurs
+      args: default
+    metrics:
+    - name: Wer
+      type: wer
+      value: 0.0756
+---
+
+<!-- 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-v3-pt-cv19-fleurs
+
+This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the fsicoli/cv19-fleurs default dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1823
+- Wer: 0.0756
+
+## 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: 10000
+- training_steps: 50000
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch   | Step  | Validation Loss | Wer    |
+|:-------------:|:-------:|:-----:|:---------------:|:------:|
+| 0.0559        | 2.2883  | 5000  | 0.1096          | 0.0730 |
+| 0.0581        | 4.5767  | 10000 | 0.1326          | 0.0829 |
+| 0.0225        | 6.8650  | 15000 | 0.1570          | 0.0849 |
+| 0.0088        | 9.1533  | 20000 | 0.1704          | 0.0840 |
+| 0.0065        | 11.4416 | 25000 | 0.1823          | 0.0849 |
+| 0.006         | 13.7300 | 30000 | 0.1808          | 0.0809 |
+| 0.0055        | 16.0183 | 35000 | 0.1811          | 0.0790 |
+| 0.0031        | 18.3066 | 40000 | 0.1907          | 0.0784 |
+| 0.0011        | 20.5950 | 45000 | 0.1852          | 0.0771 |
+| 0.0003        | 22.8833 | 50000 | 0.1848          | 0.0756 |
+
+
+### Framework versions
+
+- Transformers 4.45.0.dev0
+- Pytorch 2.4.1
+- Datasets 2.21.0
+- Tokenizers 0.19.1