Training in progress, step 50
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README.md
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---
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base_model: openai/whisper-small
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datasets:
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- artifacts/sv-SE_mozilla-foundation_common_voice_17_0
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library_name: transformers
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license: apache-2.0
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model-index:
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- name:
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results:
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- task:
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type: automatic-speech-recognition
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name: Speech-to-Text
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dataset:
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name:
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type:
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metrics:
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---
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## Evaluation results on 5259 audio samples of Swedish:
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###
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- Word Error Rate: 28.413
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- Loss: 1.066
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---
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library_name: transformers
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license: apache-2.0
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base_model: openai/whisper-small
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tags:
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- generated_from_trainer
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datasets:
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- common_voice_17_0
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metrics:
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- wer
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model-index:
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- name: whisper-small-swedish
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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: common_voice_17_0
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type: common_voice_17_0
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config: sv-SE
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split: test
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args: sv-SE
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metrics:
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- name: Wer
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type: wer
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value: 20.14691254112786
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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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# whisper-small-swedish
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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_17_0 dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3111
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- Model Preparation Time: 0.0044
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- Wer: 20.1469
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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: 1e-05
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- train_batch_size: 258
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- eval_batch_size: 64
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- seed: 42
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- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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- lr_scheduler_type: linear
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- lr_scheduler_warmup_steps: 50
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- training_steps: 1250
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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 | Model Preparation Time | Wer |
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|:-------------:|:-------:|:----:|:---------------:|:----------------------:|:-------:|
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| 0.6188 | 0.9804 | 50 | 0.3424 | 0.0044 | 23.1107 |
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| 0.2417 | 1.9608 | 100 | 0.3089 | 0.0044 | 21.0881 |
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| 0.1456 | 2.9412 | 150 | 0.3038 | 0.0044 | 20.7412 |
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| 0.0928 | 3.9216 | 200 | 0.3111 | 0.0044 | 20.1469 |
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| 0.0554 | 4.9020 | 250 | 0.3231 | 0.0044 | 20.3739 |
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| 0.035 | 5.8824 | 300 | 0.3367 | 0.0044 | 20.8432 |
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| 0.0215 | 6.8627 | 350 | 0.3619 | 0.0044 | 20.8458 |
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| 0.0143 | 7.8431 | 400 | 0.3768 | 0.0044 | 20.9299 |
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| 0.0101 | 8.8235 | 450 | 0.3880 | 0.0044 | 20.8509 |
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| 0.0084 | 9.8039 | 500 | 0.3960 | 0.0044 | 20.8993 |
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| 0.0072 | 10.7843 | 550 | 0.3999 | 0.0044 | 21.0014 |
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| 0.0059 | 11.7647 | 600 | 0.4069 | 0.0044 | 20.8942 |
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| 0.0053 | 12.7451 | 650 | 0.4130 | 0.0044 | 20.9656 |
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| 0.0047 | 13.7255 | 700 | 0.4177 | 0.0044 | 20.9963 |
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| 0.0043 | 14.7059 | 750 | 0.4208 | 0.0044 | 20.9478 |
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| 0.004 | 15.6863 | 800 | 0.4241 | 0.0044 | 21.0371 |
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| 0.0037 | 16.6667 | 850 | 0.4265 | 0.0044 | 21.0600 |
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| 0.0035 | 17.6471 | 900 | 0.4298 | 0.0044 | 21.1034 |
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| 0.0034 | 18.6275 | 950 | 0.4317 | 0.0044 | 21.0983 |
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| 0.0032 | 19.6078 | 1000 | 0.4334 | 0.0044 | 21.1416 |
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| 0.0031 | 20.5882 | 1050 | 0.4351 | 0.0044 | 21.1518 |
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| 0.003 | 21.5686 | 1100 | 0.4361 | 0.0044 | 21.1748 |
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| 0.0029 | 22.5490 | 1150 | 0.4368 | 0.0044 | 21.1620 |
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| 0.0029 | 23.5294 | 1200 | 0.4374 | 0.0044 | 21.1799 |
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| 0.0029 | 24.5098 | 1250 | 0.4377 | 0.0044 | 21.1722 |
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### Framework versions
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- Transformers 4.49.0
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- Pytorch 2.6.0+cu124
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- Datasets 3.3.2
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- Tokenizers 0.21.0
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model.safetensors
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runs/Mar06_11-07-10_gpu-pod/events.out.tfevents.1741252962.gpu-pod.61799.0
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training_args.bin
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