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whisper-large-v3-MH-fine-tuned

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  1. README.md +23 -23
  2. adapter_model.safetensors +1 -1
  3. runs/May19_12-21-14_d247403fb5a3/events.out.tfevents.1716121282.d247403fb5a3.34.1 +3 -0
  4. training_args.bin +1 -1
README.md CHANGED
@@ -16,7 +16,7 @@ should probably proofread and complete it, then remove this comment. -->
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  This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.7223
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  ## Model description
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@@ -36,12 +36,12 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 0.001
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- - train_batch_size: 4
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  - eval_batch_size: 4
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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: 14
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  - num_epochs: 20
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  - mixed_precision_training: Native AMP
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@@ -49,26 +49,26 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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- | 0.8453 | 1.0 | 7 | 0.6698 |
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- | 0.5918 | 2.0 | 14 | 0.6178 |
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- | 0.3676 | 3.0 | 21 | 0.6309 |
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- | 0.2071 | 4.0 | 28 | 0.5503 |
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- | 0.0815 | 5.0 | 35 | 0.5673 |
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- | 0.0716 | 6.0 | 42 | 0.6529 |
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- | 0.0498 | 7.0 | 49 | 0.6263 |
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- | 0.0385 | 8.0 | 56 | 0.6218 |
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- | 0.0279 | 9.0 | 63 | 0.6489 |
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- | 0.0223 | 10.0 | 70 | 0.6558 |
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- | 0.0156 | 11.0 | 77 | 0.7044 |
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- | 0.012 | 12.0 | 84 | 0.6791 |
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- | 0.0101 | 13.0 | 91 | 0.7385 |
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- | 0.3867 | 14.0 | 98 | 0.7011 |
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- | 0.0131 | 15.0 | 105 | 0.7007 |
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- | 0.0117 | 16.0 | 112 | 0.7196 |
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- | 0.0107 | 17.0 | 119 | 0.7192 |
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- | 0.0075 | 18.0 | 126 | 0.7183 |
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- | 0.0081 | 19.0 | 133 | 0.7164 |
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- | 0.0067 | 20.0 | 140 | 0.7223 |
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  ### Framework versions
 
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  This model is a fine-tuned version of [openai/whisper-large-v3](https://huggingface.co/openai/whisper-large-v3) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.6099
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  ## Model description
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  The following hyperparameters were used during training:
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  - learning_rate: 0.001
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+ - train_batch_size: 8
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  - eval_batch_size: 4
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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: 50
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  - num_epochs: 20
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  - mixed_precision_training: Native AMP
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  | Training Loss | Epoch | Step | Validation Loss |
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  |:-------------:|:-----:|:----:|:---------------:|
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+ | 1.0586 | 1.0 | 4 | 0.8056 |
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+ | 1.0643 | 2.0 | 8 | 0.6915 |
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+ | 0.7456 | 3.0 | 12 | 0.6105 |
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+ | 0.6496 | 4.0 | 16 | 0.5754 |
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+ | 0.6013 | 5.0 | 20 | 0.5447 |
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+ | 0.443 | 6.0 | 24 | 0.5263 |
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+ | 0.3267 | 7.0 | 28 | 0.5356 |
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+ | 0.2908 | 8.0 | 32 | 0.5291 |
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+ | 0.1509 | 9.0 | 36 | 0.5256 |
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+ | 0.1156 | 10.0 | 40 | 0.5158 |
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+ | 0.0715 | 11.0 | 44 | 0.5315 |
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+ | 0.0516 | 12.0 | 48 | 0.5286 |
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+ | 0.0457 | 13.0 | 52 | 0.5434 |
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+ | 0.048 | 14.0 | 56 | 0.5550 |
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+ | 0.0297 | 15.0 | 60 | 0.5781 |
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+ | 0.0213 | 16.0 | 64 | 0.5890 |
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+ | 0.0198 | 17.0 | 68 | 0.6000 |
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+ | 0.0175 | 18.0 | 72 | 0.6046 |
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+ | 0.0158 | 19.0 | 76 | 0.6101 |
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+ | 0.0128 | 20.0 | 80 | 0.6099 |
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  ### Framework versions
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