End of training
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README.md
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- generated_from_trainer
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datasets:
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- bond005/sberdevices_golos_10h_crowd
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model-index:
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- name: my_model - Val123val
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results:
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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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# my_model - Val123val
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Sberdevices_golos_10h_crowd dataset.
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 1e-05
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- train_batch_size:
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- eval_batch_size:
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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_steps: 500
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- training_steps:
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### Framework versions
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- Transformers 4.36.2
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- Pytorch 2.1.
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- Datasets 2.16.
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- Tokenizers 0.15.0
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- generated_from_trainer
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datasets:
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- bond005/sberdevices_golos_10h_crowd
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metrics:
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- wer
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model-index:
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- name: my_model - Val123val
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results:
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- task:
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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: Sberdevices_golos_10h_crowd
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type: bond005/sberdevices_golos_10h_crowd
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args: 'split: test'
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metrics:
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- name: Wer
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type: wer
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value: 42.241139818232334
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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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# my_model - Val123val
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Sberdevices_golos_10h_crowd dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1761
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- Wer: 42.2411
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## Model description
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The following hyperparameters were used during training:
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- learning_rate: 1e-05
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- train_batch_size: 16
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- eval_batch_size: 8
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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_steps: 500
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- training_steps: 5000
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|
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| 0.1521 | 0.91 | 500 | 0.1824 | 29.3408 |
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| 0.0824 | 1.82 | 1000 | 0.1702 | 27.5291 |
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| 0.0304 | 2.73 | 1500 | 0.1726 | 45.1046 |
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| 0.0114 | 3.64 | 2000 | 0.1704 | 40.1238 |
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| 0.0039 | 4.55 | 2500 | 0.1692 | 32.1903 |
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| 0.0013 | 5.45 | 3000 | 0.1704 | 34.0298 |
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| 0.0029 | 6.36 | 3500 | 0.1712 | 39.8976 |
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| 0.0007 | 7.27 | 4000 | 0.1738 | 39.4273 |
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| 0.0006 | 8.18 | 4500 | 0.1755 | 41.0664 |
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| 0.0005 | 9.09 | 5000 | 0.1761 | 42.2411 |
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### Framework versions
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- Transformers 4.36.2
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- Pytorch 2.1.2+cpu
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- Datasets 2.16.0
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- Tokenizers 0.15.0
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model.safetensors
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runs/Dec28_00-23-15_DESKTOP-1CUM2VF/events.out.tfevents.1703713101.DESKTOP-1CUM2VF.30008.0
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