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--- |
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license: cc-by-nc-4.0 |
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base_model: facebook/mms-1b-all |
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tags: |
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- generated_from_trainer |
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datasets: |
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- audiofolder |
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metrics: |
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- wer |
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model-index: |
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- name: hindi_fb1mms_timebalancedreg |
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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: audiofolder |
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type: audiofolder |
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config: default |
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split: train |
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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: 0.4259275985404097 |
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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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# hindi_fb1mms_timebalancedreg |
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This model is a fine-tuned version of [facebook/mms-1b-all](https://huggingface.co/facebook/mms-1b-all) on the audiofolder dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7182 |
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- Wer: 0.4259 |
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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: 0.0002 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 32 |
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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: 100 |
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- num_epochs: 30 |
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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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| 4.087 | 1.0191 | 400 | 3.5884 | 0.9998 | |
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| 3.935 | 2.0382 | 800 | 3.4190 | 0.9959 | |
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| 3.3712 | 3.0573 | 1200 | 3.3003 | 0.9709 | |
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| 3.2027 | 4.0764 | 1600 | 2.8687 | 0.9861 | |
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| 1.4667 | 5.0955 | 2000 | 0.6547 | 0.4129 | |
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| 1.2468 | 6.1146 | 2400 | 0.6031 | 0.3955 | |
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| 1.2401 | 7.1338 | 2800 | 0.6334 | 0.4172 | |
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| 1.2952 | 8.1529 | 3200 | 0.6857 | 0.4238 | |
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| 1.2466 | 9.1720 | 3600 | 0.7279 | 0.4361 | |
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| 1.2094 | 10.1911 | 4000 | 0.6768 | 0.4140 | |
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| 1.1764 | 11.2102 | 4400 | 0.6735 | 0.4234 | |
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| 1.1491 | 12.2293 | 4800 | 0.7047 | 0.4334 | |
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| 1.1504 | 13.2484 | 5200 | 0.6704 | 0.4215 | |
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| 1.1656 | 14.2675 | 5600 | 0.6684 | 0.4207 | |
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| 1.1666 | 15.2866 | 6000 | 0.7367 | 0.4339 | |
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| 1.1512 | 16.3057 | 6400 | 0.7384 | 0.4386 | |
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| 1.1646 | 17.3248 | 6800 | 0.7087 | 0.4251 | |
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| 1.1407 | 18.3439 | 7200 | 0.7192 | 0.4329 | |
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| 1.1207 | 19.3631 | 7600 | 0.7141 | 0.4236 | |
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| 1.1145 | 20.3822 | 8000 | 0.7503 | 0.4374 | |
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| 1.1138 | 21.4013 | 8400 | 0.7235 | 0.4278 | |
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| 1.1091 | 22.4204 | 8800 | 0.7468 | 0.4404 | |
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| 1.1255 | 23.4395 | 9200 | 0.7177 | 0.4264 | |
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| 1.0959 | 24.4586 | 9600 | 0.7050 | 0.4191 | |
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| 1.106 | 25.4777 | 10000 | 0.7420 | 0.4337 | |
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| 1.0949 | 26.4968 | 10400 | 0.7063 | 0.4223 | |
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| 1.1142 | 27.5159 | 10800 | 0.7170 | 0.4257 | |
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| 1.1076 | 28.5350 | 11200 | 0.7223 | 0.4267 | |
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| 1.1028 | 29.5541 | 11600 | 0.7182 | 0.4259 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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