End of training
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README.md
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---
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language:
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- ro
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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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- hf-asr-leaderboard
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- generated_from_trainer
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datasets:
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- VladS159/common_voice_romanian_speech_synthesis
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metrics:
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- wer
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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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name: Automatic Speech Recognition
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type: automatic-speech-recognition
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dataset:
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name: Common Voice 16.1 + Romanian speech synthesis
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type: VladS159/common_voice_romanian_speech_synthesis
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args: 'config: ro, split: test'
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metrics:
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- name: Wer
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type: wer
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value: 12.181988686208669
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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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#
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Wer:
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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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- distributed_type: multi-GPU
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- num_devices: 3
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- total_train_batch_size:
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- total_eval_batch_size:
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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:
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- training_steps:
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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 | Wer |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|
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| 0.
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| 0.
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| 0.
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| 0.
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| 0.0139 | 4.9 | 1250 | 0.1409 | 11.9702 |
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| 0.0076 | 5.88 | 1500 | 0.1539 | 12.0459 |
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| 0.005 | 6.86 | 1750 | 0.1599 | 12.1880 |
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| 0.0039 | 7.84 | 2000 | 0.1620 | 12.1820 |
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### Framework versions
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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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metrics:
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- wer
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model-index:
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- name: Whisper_medium_ro_VladS_1000_steps_multi_gpu_25_02_2024
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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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should probably proofread and complete it, then remove this comment. -->
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# Whisper_medium_ro_VladS_1000_steps_multi_gpu_25_02_2024
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1247
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- Wer: 11.7262
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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: 10
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- eval_batch_size: 10
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 3
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- total_train_batch_size: 30
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- total_eval_batch_size: 30
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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: 100
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- training_steps: 1000
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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 | Wer |
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|:-------------:|:-----:|:----:|:---------------:|:-------:|
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| 0.1447 | 0.61 | 250 | 0.1532 | 13.8768 |
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| 0.0599 | 1.23 | 500 | 0.1305 | 12.5141 |
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| 0.0595 | 1.84 | 750 | 0.1256 | 12.3255 |
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| 0.032 | 2.46 | 1000 | 0.1247 | 11.7262 |
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### Framework versions
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runs/Feb25_02-35-41_ubuntu-llama/events.out.tfevents.1708821359.ubuntu-llama.190234.0
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