End of training
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README.md
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---
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license: apache-2.0
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base_model: openai/whisper-medium
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tags:
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- generated_from_trainer
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datasets:
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- audiofolder
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metrics:
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- accuracy
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model-index:
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- name: Pak-Speech-Processing/urdu-emotion-whisper
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results:
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- task:
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name: Audio Classification
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type: audio-classification
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dataset:
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name: Pak-Speech-Processing/urdu-emotions
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type: audiofolder
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config: default
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split: train
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args: default
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.9166666666666666
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# Pak-Speech-Processing/urdu-emotion-whisper
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Pak-Speech-Processing/urdu-emotions dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.5604
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- Accuracy: 0.9167
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 2
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- eval_batch_size: 2
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- seed: 42
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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: 10
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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 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 0.0018 | 1.0 | 120 | 2.0096 | 0.6667 |
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| 0.5139 | 2.0 | 240 | 0.8303 | 0.8667 |
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| 0.6903 | 3.0 | 360 | 0.8813 | 0.8833 |
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| 0.0006 | 4.0 | 480 | 0.3012 | 0.95 |
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| 1.5207 | 5.0 | 600 | 0.6310 | 0.8833 |
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| 0.0005 | 6.0 | 720 | 0.5993 | 0.9 |
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| 0.0004 | 7.0 | 840 | 0.3247 | 0.9167 |
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| 0.0001 | 8.0 | 960 | 0.5303 | 0.9167 |
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| 0.0001 | 9.0 | 1080 | 0.5530 | 0.9167 |
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| 0.0001 | 10.0 | 1200 | 0.5604 | 0.9167 |
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### Framework versions
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- Transformers 4.39.0.dev0
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- Pytorch 2.2.1+cu121
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- Datasets 2.18.0
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- Tokenizers 0.15.2
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model.safetensors
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