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--- |
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license: apache-2.0 |
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base_model: Harveenchadha/hindi_base_wav2vec2 |
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tags: |
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- generated_from_trainer |
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metrics: |
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- wer |
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model-index: |
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- name: hindi_wav2vec2_optimized_2 |
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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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# hindi_wav2vec2_optimized_2 |
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This model is a fine-tuned version of [Harveenchadha/hindi_base_wav2vec2](https://huggingface.co/Harveenchadha/hindi_base_wav2vec2) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6089 |
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- Wer: 0.1899 |
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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: 0.0003 |
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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: 10 |
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- num_epochs: 100 |
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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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| 0.2406 | 5.56 | 25 | 0.5544 | 0.3418 | |
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| 0.0725 | 11.11 | 50 | 0.4668 | 0.2426 | |
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| 0.0437 | 16.67 | 75 | 0.6185 | 0.2405 | |
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| 0.0344 | 22.22 | 100 | 0.5553 | 0.2257 | |
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| 0.0311 | 27.78 | 125 | 0.5775 | 0.2300 | |
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| 0.0287 | 33.33 | 150 | 0.7120 | 0.2110 | |
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| 0.0242 | 38.89 | 175 | 0.7068 | 0.2152 | |
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| 0.0175 | 44.44 | 200 | 0.5265 | 0.2384 | |
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| 0.0128 | 50.0 | 225 | 0.5554 | 0.2300 | |
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| 0.0114 | 55.56 | 250 | 0.6330 | 0.2300 | |
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| 0.0105 | 61.11 | 275 | 0.6020 | 0.2194 | |
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| 0.0052 | 66.67 | 300 | 0.6073 | 0.2152 | |
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| 0.0041 | 72.22 | 325 | 0.5865 | 0.1941 | |
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| 0.0074 | 77.78 | 350 | 0.6138 | 0.1983 | |
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| 0.0033 | 83.33 | 375 | 0.6106 | 0.1920 | |
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| 0.0074 | 88.89 | 400 | 0.6089 | 0.1899 | |
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### Framework versions |
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- Transformers 4.34.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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