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--- |
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library_name: transformers |
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language: |
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- lv |
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license: apache-2.0 |
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base_model: FelixK7/whisper-medium-lv |
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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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- mozilla-foundation/common_voice_16_1 |
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metrics: |
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- wer |
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model-index: |
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- name: Whisper medium LV - Felikss Kleins |
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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 |
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type: mozilla-foundation/common_voice_16_1 |
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config: lv |
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split: None |
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args: 'config: lv, split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 9.459716154242761 |
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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 LV - Felikss Kleins |
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This model is a fine-tuned version of [FelixK7/whisper-medium-lv](https://huggingface.co/FelixK7/whisper-medium-lv) on the Common Voice 16.1 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2053 |
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- Wer: 9.4597 |
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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: 3e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 64 |
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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: 10000 |
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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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| No log | 0.02 | 200 | 0.1318 | 7.6741 | |
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| 0.0445 | 1.0199 | 400 | 0.1527 | 8.4475 | |
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| 0.0338 | 2.0199 | 600 | 0.1703 | 9.7148 | |
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| 0.0345 | 3.0198 | 800 | 0.1725 | 9.7392 | |
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| 0.0311 | 4.0198 | 1000 | 0.1789 | 9.8830 | |
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| 0.0311 | 5.0198 | 1200 | 0.1792 | 10.0187 | |
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| 0.0288 | 6.0197 | 1400 | 0.1858 | 9.6063 | |
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| 0.0237 | 7.0197 | 1600 | 0.1839 | 9.8803 | |
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| 0.022 | 8.0196 | 1800 | 0.1847 | 10.2955 | |
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| 0.0198 | 9.0196 | 2000 | 0.1878 | 9.8885 | |
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| 0.0198 | 10.0195 | 2200 | 0.1909 | 9.9237 | |
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| 0.0183 | 11.0195 | 2400 | 0.1948 | 10.1924 | |
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| 0.0161 | 12.0194 | 2600 | 0.1951 | 10.4122 | |
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| 0.0154 | 13.0193 | 2800 | 0.1952 | 9.9997 | |
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| 0.0141 | 14.0193 | 3000 | 0.1972 | 10.1001 | |
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| 0.0141 | 15.0192 | 3200 | 0.1976 | 10.1544 | |
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| 0.0118 | 16.0192 | 3400 | 0.2014 | 10.4258 | |
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| 0.0115 | 17.0191 | 3600 | 0.2021 | 10.6890 | |
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| 0.0106 | 18.0191 | 3800 | 0.2005 | 10.1951 | |
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| 0.0092 | 19.0191 | 4000 | 0.2022 | 10.4638 | |
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| 0.0092 | 20.019 | 4200 | 0.2003 | 10.0947 | |
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| 0.0089 | 21.0190 | 4400 | 0.2043 | 9.8776 | |
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| 0.0085 | 22.0189 | 4600 | 0.2063 | 10.4719 | |
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| 0.0083 | 23.0189 | 4800 | 0.2067 | 10.0540 | |
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| 0.0069 | 24.0188 | 5000 | 0.2058 | 9.7908 | |
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| 0.0069 | 25.0188 | 5200 | 0.2056 | 10.4583 | |
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| 0.0078 | 26.0187 | 5400 | 0.2090 | 10.1843 | |
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| 0.0063 | 27.0187 | 5600 | 0.2096 | 10.2250 | |
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| 0.0058 | 28.0186 | 5800 | 0.2047 | 10.2602 | |
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| 0.0052 | 29.0186 | 6000 | 0.2087 | 9.9319 | |
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| 0.0052 | 30.0185 | 6200 | 0.2040 | 10.0811 | |
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| 0.0054 | 31.0185 | 6400 | 0.2081 | 9.9482 | |
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| 0.0045 | 32.0184 | 6600 | 0.2063 | 9.6849 | |
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| 0.004 | 33.0183 | 6800 | 0.2077 | 10.0052 | |
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| 0.0035 | 34.0183 | 7000 | 0.2105 | 10.1056 | |
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| 0.0035 | 35.0183 | 7200 | 0.2075 | 9.6985 | |
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| 0.0035 | 36.0182 | 7400 | 0.2075 | 9.6063 | |
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| 0.003 | 37.0181 | 7600 | 0.2115 | 9.8396 | |
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| 0.0027 | 38.0181 | 7800 | 0.2061 | 9.5601 | |
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| 0.0025 | 39.0181 | 8000 | 0.2082 | 9.6252 | |
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| 0.0025 | 40.018 | 8200 | 0.2052 | 9.5520 | |
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| 0.0023 | 41.0179 | 8400 | 0.2060 | 9.7826 | |
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| 0.0024 | 42.0179 | 8600 | 0.2083 | 9.6361 | |
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| 0.002 | 43.0179 | 8800 | 0.2069 | 9.5981 | |
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| 0.0021 | 44.0178 | 9000 | 0.2051 | 9.3892 | |
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| 0.0021 | 45.0177 | 9200 | 0.2054 | 9.3756 | |
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| 0.0019 | 46.0177 | 9400 | 0.2049 | 9.5167 | |
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| 0.0017 | 47.0177 | 9600 | 0.2051 | 9.4733 | |
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| 0.0017 | 48.0176 | 9800 | 0.2050 | 9.4923 | |
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| 0.0014 | 49.0175 | 10000 | 0.2053 | 9.4597 | |
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### Framework versions |
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- Transformers 4.45.0.dev0 |
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- Pytorch 2.0.1 |
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- Datasets 3.0.0 |
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- Tokenizers 0.19.1 |
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