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Browse files- README.md +18 -19
- all_results.json +5 -5
- eval_results.json +6 -6
README.md
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@@ -4,36 +4,34 @@ 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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metrics:
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- wer
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model-index:
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- name: whisper-
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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:
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type:
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split: test
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args: pt
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metrics:
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- name: Wer
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type: wer
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value: 0.
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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-
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the
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It achieves the following results on the evaluation set:
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- Loss: 0.
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- Wer: 0.
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## Model description
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 2
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-
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- total_eval_batch_size: 2
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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: 5000
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- mixed_precision_training: Native AMP
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:-----:|:----:|:---------------:|:------:|
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### Framework versions
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tags:
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- generated_from_trainer
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datasets:
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- fsicoli/cv16-fleurs
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metrics:
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- wer
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model-index:
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- name: whisper-medium-pt-cv16-fleurs
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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: fsicoli/cv16-fleurs default
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type: fsicoli/cv16-fleurs
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args: default
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metrics:
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- name: Wer
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type: wer
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value: 0.09421927983206846
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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-pt-cv16-fleurs
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This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the fsicoli/cv16-fleurs default dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1409
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- Wer: 0.0942
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## Model description
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 2
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- gradient_accumulation_steps: 16
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- total_train_batch_size: 32
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- total_eval_batch_size: 2
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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: 5000
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- training_steps: 5000
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- mixed_precision_training: Native AMP
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:-----:|:----:|:---------------:|:------:|
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| 0.2552 | 0.93 | 1000 | 0.2200 | 0.1220 |
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| 0.1928 | 1.87 | 2000 | 0.1645 | 0.1062 |
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| 0.1646 | 2.8 | 3000 | 0.1508 | 0.1016 |
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| 0.1333 | 3.74 | 4000 | 0.1438 | 0.0970 |
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| 0.1027 | 4.67 | 5000 | 0.1409 | 0.0942 |
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### Framework versions
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all_results.json
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{
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"epoch": 4.67,
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"eval_loss": 0.
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"eval_runtime":
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"eval_samples": 9414,
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"eval_samples_per_second": 1.
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"eval_steps_per_second": 0.
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"eval_wer": 0.
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"train_loss": 0.2694411336898804,
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"train_runtime": 106369.5753,
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"train_samples": 34267,
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{
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"epoch": 4.67,
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"eval_loss": 0.14086556434631348,
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"eval_runtime": 7908.2656,
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"eval_samples": 9414,
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"eval_samples_per_second": 1.19,
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"eval_steps_per_second": 0.595,
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"eval_wer": 0.09421927983206846,
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"train_loss": 0.2694411336898804,
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"train_runtime": 106369.5753,
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"train_samples": 34267,
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eval_results.json
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{
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"epoch":
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"eval_loss": 0.
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"eval_runtime":
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"eval_samples": 9414,
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"eval_samples_per_second": 1.
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"eval_steps_per_second": 0.
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"eval_wer": 0.
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}
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{
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"epoch": 4.67,
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"eval_loss": 0.14086556434631348,
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"eval_runtime": 7908.2656,
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"eval_samples": 9414,
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"eval_samples_per_second": 1.19,
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"eval_steps_per_second": 0.595,
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"eval_wer": 0.09421927983206846
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}
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