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yuweiiizz
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whisper-small-taiwanese-lora

PEFT
TensorBoard
Safetensors
Min Nan Chinese
Generated from Trainer
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  1. README.md +10 -17
  2. adapter_model.safetensors +1 -1
  3. runs/Sep05_19-23-14_8fedde53f142/events.out.tfevents.1725564195.8fedde53f142.25.0 +2 -2
README.md CHANGED
@@ -1,13 +1,13 @@
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  ---
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- base_model: openai/whisper-small
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- datasets:
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- - mozilla-foundation/common_voice_16_1
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  language:
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  - nan
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- library_name: peft
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  license: apache-2.0
 
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  tags:
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  - generated_from_trainer
 
 
 
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  model-index:
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  - name: Whisper small Taiwanese - LoRA
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  results: []
@@ -20,7 +20,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 16.1 dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.9306
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  ## Model description
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@@ -48,22 +48,15 @@ The following hyperparameters were used during training:
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.1
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- - num_epochs: 9
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  - mixed_precision_training: Native AMP
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  ### Training results
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- | Training Loss | Epoch | Step | Validation Loss |
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- |:-------------:|:-----:|:-----:|:---------------:|
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- | 1.0057 | 1.0 | 2528 | 1.0098 |
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- | 0.846 | 2.0 | 5056 | 0.9359 |
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- | 0.7486 | 3.0 | 7585 | 0.8879 |
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- | 0.6056 | 4.0 | 10112 | 0.8839 |
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- | 0.4569 | 5.0 | 12640 | 0.9000 |
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- | 0.4929 | 6.0 | 15169 | 0.8907 |
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- | 0.3831 | 7.0 | 17696 | 0.9161 |
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- | 0.379 | 8.0 | 20225 | 0.9116 |
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- | 0.3041 | 9.0 | 22752 | 0.9306 |
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  ### Framework versions
 
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  ---
 
 
 
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  language:
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  - nan
 
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  license: apache-2.0
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+ library_name: peft
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  tags:
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  - generated_from_trainer
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+ datasets:
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+ - mozilla-foundation/common_voice_16_1
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+ base_model: openai/whisper-small
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  model-index:
12
  - name: Whisper small Taiwanese - LoRA
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  results: []
 
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  This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 16.1 dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.9143
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  ## Model description
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.1
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+ - num_epochs: 2
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  - mixed_precision_training: Native AMP
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  ### Training results
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:----:|:---------------:|
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+ | 1.0204 | 1.0 | 2572 | 1.0091 |
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+ | 0.8829 | 2.0 | 5144 | 0.9143 |
 
 
 
 
 
 
 
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  ### Framework versions
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