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--- |
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base_model: openai/whisper-small |
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datasets: |
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- mozilla-foundation/common_voice_13_0 |
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language: |
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- multilingual |
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library_name: peft |
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license: apache-2.0 |
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tags: |
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- hf-asr-leaderboard |
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- generated_from_trainer |
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model-index: |
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- name: Whisper Small 2 lang LORA 2nd Settings |
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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 Small 2 lang LORA 2nd Settings |
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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 13.0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2569 |
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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: 4 |
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- eval_batch_size: 1 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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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: 20000 |
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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 | |
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|:-------------:|:------:|:-----:|:---------------:| |
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| 1.9564 | 0.1002 | 250 | 2.1385 | |
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| 1.2046 | 0.2004 | 500 | 1.1713 | |
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| 0.8719 | 0.3006 | 750 | 0.9414 | |
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| 0.7799 | 0.4008 | 1000 | 0.8261 | |
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| 0.6956 | 0.5010 | 1250 | 0.6536 | |
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| 0.3536 | 0.6012 | 1500 | 0.2990 | |
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| 0.3167 | 0.7014 | 1750 | 0.2902 | |
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| 0.3252 | 0.8016 | 2000 | 0.2850 | |
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| 0.3133 | 0.9018 | 2250 | 0.2821 | |
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| 0.3764 | 1.0020 | 2500 | 0.2800 | |
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| 0.2942 | 1.1022 | 2750 | 0.2775 | |
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| 0.2937 | 1.2024 | 3000 | 0.2770 | |
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| 0.3478 | 1.3026 | 3250 | 0.2745 | |
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| 0.3776 | 1.4028 | 3500 | 0.2729 | |
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| 0.3099 | 1.5030 | 3750 | 0.2713 | |
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| 0.3087 | 1.6032 | 4000 | 0.2705 | |
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| 0.2998 | 1.7034 | 4250 | 0.2699 | |
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| 0.3226 | 1.8036 | 4500 | 0.2683 | |
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| 0.3589 | 1.9038 | 4750 | 0.2676 | |
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| 0.3411 | 2.0040 | 5000 | 0.2673 | |
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| 0.3084 | 2.1042 | 5250 | 0.2674 | |
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| 0.31 | 2.2044 | 5500 | 0.2663 | |
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| 0.3388 | 2.3046 | 5750 | 0.2657 | |
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| 0.2716 | 2.4048 | 6000 | 0.2652 | |
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| 0.3059 | 2.5050 | 6250 | 0.2652 | |
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| 0.27 | 2.6052 | 6500 | 0.2648 | |
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| 0.2954 | 2.7054 | 6750 | 0.2639 | |
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| 0.336 | 2.8056 | 7000 | 0.2641 | |
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| 0.2833 | 2.9058 | 7250 | 0.2631 | |
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| 0.2777 | 3.0060 | 7500 | 0.2624 | |
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| 0.2418 | 3.1062 | 7750 | 0.2618 | |
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| 0.3194 | 3.2064 | 8000 | 0.2623 | |
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| 0.3319 | 3.3066 | 8250 | 0.2623 | |
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| 0.3551 | 3.4068 | 8500 | 0.2615 | |
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| 0.3421 | 3.5070 | 8750 | 0.2619 | |
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| 0.3862 | 3.6072 | 9000 | 0.2616 | |
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| 0.2437 | 3.7074 | 9250 | 0.2609 | |
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| 0.2995 | 3.8076 | 9500 | 0.2604 | |
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| 0.3535 | 3.9078 | 9750 | 0.2603 | |
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| 0.2871 | 4.0080 | 10000 | 0.2601 | |
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| 0.2908 | 4.1082 | 10250 | 0.2604 | |
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| 0.3203 | 4.2084 | 10500 | 0.2599 | |
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| 0.2598 | 4.3086 | 10750 | 0.2594 | |
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| 0.2942 | 4.4088 | 11000 | 0.2593 | |
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| 0.3302 | 4.5090 | 11250 | 0.2590 | |
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| 0.3615 | 4.6092 | 11500 | 0.2584 | |
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| 0.3291 | 4.7094 | 11750 | 0.2582 | |
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| 0.2781 | 4.8096 | 12000 | 0.2588 | |
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| 0.3106 | 4.9098 | 12250 | 0.2585 | |
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| 0.2484 | 5.0100 | 12500 | 0.2583 | |
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| 0.2645 | 5.1102 | 12750 | 0.2583 | |
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| 0.3034 | 5.2104 | 13000 | 0.2581 | |
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| 0.2865 | 5.3106 | 13250 | 0.2576 | |
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| 0.3301 | 5.4108 | 13500 | 0.2580 | |
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| 0.3759 | 5.5110 | 13750 | 0.2579 | |
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| 0.3318 | 5.6112 | 14000 | 0.2581 | |
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| 0.2825 | 5.7114 | 14250 | 0.2579 | |
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| 0.2976 | 5.8116 | 14500 | 0.2578 | |
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| 0.2976 | 5.9118 | 14750 | 0.2577 | |
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| 0.3681 | 6.0120 | 15000 | 0.2575 | |
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| 0.3274 | 6.1122 | 15250 | 0.2575 | |
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| 0.2948 | 6.2124 | 15500 | 0.2577 | |
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| 0.2932 | 6.3126 | 15750 | 0.2576 | |
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| 0.2587 | 6.4128 | 16000 | 0.2578 | |
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| 0.2564 | 6.5130 | 16250 | 0.2573 | |
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| 0.2776 | 6.6132 | 16500 | 0.2569 | |
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| 0.2954 | 6.7134 | 16750 | 0.2569 | |
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| 0.2891 | 6.8136 | 17000 | 0.2568 | |
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| 0.2373 | 6.9138 | 17250 | 0.2569 | |
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| 0.3532 | 7.0140 | 17500 | 0.2569 | |
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| 0.2676 | 7.1142 | 17750 | 0.2569 | |
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| 0.2763 | 7.2144 | 18000 | 0.2569 | |
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| 0.2692 | 7.3146 | 18250 | 0.2571 | |
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| 0.3198 | 7.4148 | 18500 | 0.2570 | |
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| 0.2158 | 7.5150 | 18750 | 0.2571 | |
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| 0.277 | 7.6152 | 19000 | 0.2572 | |
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| 0.2308 | 7.7154 | 19250 | 0.2572 | |
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| 0.3166 | 7.8156 | 19500 | 0.2569 | |
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| 0.3064 | 7.9158 | 19750 | 0.2570 | |
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| 0.2743 | 8.0160 | 20000 | 0.2569 | |
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### Framework versions |
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- PEFT 0.11.2.dev0 |
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- Transformers 4.43.0.dev0 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
