Model save

README.md

@@ -1,86 +1,91 @@
----
-language:
-- zh
-license: apache-2.0
-base_model: openai/whisper-small
-tags:
-- generated_from_trainer
-datasets:
-- edmundchan70/Cantonese_fine_tune
-metrics:
-- wer
-model-index:
-- name: Whisper Small fine tune test - Edmund
-  results:
-  - task:
-      name: Automatic Speech Recognition
-      type: automatic-speech-recognition
-    dataset:
-      name: Preach_speech_finetuning
-      type: edmundchan70/Cantonese_fine_tune
-      args: 'config: chinese, split: test'
-    metrics:
-    - name: Wer
-      type: wer
-      value: 30.744849445324878
----
-
-<!-- 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 fine tune test - Edmund
-
-This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Preach_speech_finetuning dataset.
-It achieves the following results on the evaluation set:
-- Loss: 0.1941
-- Wer: 30.7448
-
-## 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: 1.25e-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_ratio: 0.1
-- num_epochs: 10
-- mixed_precision_training: Native AMP
-
-### Training results
-
-| Training Loss | Epoch | Step | Validation Loss | Wer     |
-|:-------------:|:-----:|:----:|:---------------:|:-------:|
-| No log        | 1.0   | 156  | 0.1469          | 22.1870 |
-| No log        | 2.0   | 312  | 0.1667          | 27.2583 |
-| No log        | 3.0   | 468  | 0.1770          | 27.7338 |
-| 0.0778        | 4.0   | 624  | 0.1847          | 29.7940 |
-| 0.0778        | 5.0   | 780  | 0.1970          | 30.4279 |
-| 0.0778        | 6.0   | 936  | 0.1845          | 29.7940 |
-| 0.0083        | 7.0   | 1092 | 0.1922          | 30.2694 |
-| 0.0083        | 8.0   | 1248 | 0.1926          | 29.6355 |
-| 0.0083        | 9.0   | 1404 | 0.1932          | 30.1109 |
-| 0.0009        | 10.0  | 1560 | 0.1941          | 30.7448 |
-
-
-### Framework versions
-
-- Transformers 4.44.0
-- Pytorch 2.3.1+cu121
-- Datasets 2.21.0
-- Tokenizers 0.19.1
+---
+license: apache-2.0
+base_model: edmundchan70/Cantonese_finetune_whisper
+tags:
+- generated_from_trainer
+datasets:
+- audiofolder
+metrics:
+- wer
+model-index:
+- name: model_output
+  results:
+  - task:
+      name: Automatic Speech Recognition
+      type: automatic-speech-recognition
+    dataset:
+      name: audiofolder
+      type: audiofolder
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Wer
+      type: wer
+      value: 30.476190476190478
+---
+
+<!-- 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. -->
+
+# model_output
+
+This model is a fine-tuned version of [edmundchan70/Cantonese_finetune_whisper](https://huggingface.co/edmundchan70/Cantonese_finetune_whisper) on the audiofolder dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.1966
+- Wer: 30.4762
+
+## 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: 1.25e-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_ratio: 0.1
+- num_epochs: 15
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Wer     |
+|:-------------:|:-----:|:----:|:---------------:|:-------:|
+| No log        | 1.0   | 156  | 0.1196          | 17.1429 |
+| No log        | 2.0   | 312  | 0.1553          | 24.6032 |
+| No log        | 3.0   | 468  | 0.1655          | 26.5079 |
+| 0.0806        | 4.0   | 624  | 0.1820          | 29.5238 |
+| 0.0806        | 5.0   | 780  | 0.1792          | 30.1587 |
+| 0.0806        | 6.0   | 936  | 0.1998          | 31.5873 |
+| 0.0131        | 7.0   | 1092 | 0.1954          | 31.2698 |
+| 0.0131        | 8.0   | 1248 | 0.1923          | 30.6349 |
+| 0.0131        | 9.0   | 1404 | 0.1905          | 31.2698 |
+| 0.0016        | 10.0  | 1560 | 0.1954          | 31.2698 |
+| 0.0016        | 11.0  | 1716 | 0.1931          | 31.1111 |
+| 0.0016        | 12.0  | 1872 | 0.1953          | 30.4762 |
+| 0.0005        | 13.0  | 2028 | 0.1960          | 30.6349 |
+| 0.0005        | 14.0  | 2184 | 0.1964          | 30.6349 |
+| 0.0005        | 15.0  | 2340 | 0.1966          | 30.4762 |
+
+
+### Framework versions
+
+- Transformers 4.44.0
+- Pytorch 2.4.0+cu124
+- Datasets 2.21.0
+- Tokenizers 0.19.1

generation_config.json

@@ -1,256 +1,256 @@
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+}

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