shreyasdesaisuperU
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End of training
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README.md
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@@ -18,8 +18,8 @@ should probably proofread and complete it, then remove this comment. -->
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss:
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- Wer:
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## Model description
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- train_batch_size: 2
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- eval_batch_size: 2
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- seed: 42
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- gradient_accumulation_steps:
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- total_train_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: 500
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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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| 0.0 | 2100.0 | 2100 | 5.6287 | 56.8075 |
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| 0.0 | 2200.0 | 2200 | 5.6852 | 56.3380 |
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| 0.0 | 2300.0 | 2300 | 5.7374 | 56.3380 |
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| 0.0 | 2400.0 | 2400 | 5.8023 | 56.3380 |
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| 0.0 | 2500.0 | 2500 | 5.8672 | 57.2770 |
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| 0.0 | 2600.0 | 2600 | 5.9427 | 57.2770 |
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| 0.0 | 2700.0 | 2700 | 5.9891 | 57.2770 |
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| 0.0 | 2800.0 | 2800 | 6.0490 | 57.2770 |
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| 0.0 | 2900.0 | 2900 | 6.0639 | 57.2770 |
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| 0.0 | 3000.0 | 3000 | 6.1095 | 57.2770 |
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| 0.0 | 3100.0 | 3100 | 6.1477 | 57.2770 |
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| 0.0 | 3200.0 | 3200 | 6.2039 | 57.2770 |
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| 0.0 | 3300.0 | 3300 | 6.2346 | 57.2770 |
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| 0.0 | 3400.0 | 3400 | 6.2567 | 57.2770 |
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| 0.0 | 3500.0 | 3500 | 6.2841 | 57.2770 |
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| 0.0 | 3600.0 | 3600 | 6.3028 | 57.2770 |
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| 0.0 | 3700.0 | 3700 | 6.3029 | 57.2770 |
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| 0.0 | 3800.0 | 3800 | 6.3294 | 57.2770 |
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| 0.0 | 3900.0 | 3900 | 6.3346 | 57.2770 |
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| 0.0 | 4000.0 | 4000 | 6.3374 | 57.2770 |
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### Framework versions
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 3.2716
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- Wer: 96.2441
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## Model description
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- train_batch_size: 2
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- eval_batch_size: 2
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- seed: 42
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- gradient_accumulation_steps: 8
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- total_train_batch_size: 16
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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: 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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| 0.0 | 50.0 | 50 | 3.7169 | 94.3662 |
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| 0.0 | 100.0 | 100 | 3.7773 | 102.3474 |
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| 0.0 | 150.0 | 150 | 3.8105 | 102.3474 |
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| 0.0 | 200.0 | 200 | 3.9007 | 101.8779 |
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| 0.0028 | 250.0 | 250 | 3.2200 | 90.6103 |
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| 0.0 | 300.0 | 300 | 3.1754 | 93.8967 |
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| 0.0 | 350.0 | 350 | 3.1945 | 96.2441 |
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| 0.0 | 400.0 | 400 | 3.2104 | 96.2441 |
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| 0.0 | 450.0 | 450 | 3.2225 | 96.2441 |
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| 0.0 | 500.0 | 500 | 3.2327 | 96.2441 |
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| 0.0 | 550.0 | 550 | 3.2437 | 96.2441 |
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| 0.0 | 600.0 | 600 | 3.2501 | 96.2441 |
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| 0.0 | 650.0 | 650 | 3.2550 | 96.2441 |
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| 0.0 | 700.0 | 700 | 3.2601 | 96.2441 |
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| 0.0 | 750.0 | 750 | 3.2634 | 96.2441 |
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| 0.0 | 800.0 | 800 | 3.2663 | 96.2441 |
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| 0.0 | 850.0 | 850 | 3.2691 | 96.2441 |
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| 0.0 | 900.0 | 900 | 3.2717 | 96.2441 |
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| 0.0 | 950.0 | 950 | 3.2719 | 96.2441 |
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| 0.0 | 1000.0 | 1000 | 3.2716 | 96.2441 |
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### Framework versions
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