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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-base-960h |
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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: wav2vec2-base-Malyalam-large |
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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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# wav2vec2-base-Malyalam-large |
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This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co./facebook/wav2vec2-base-960h) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4124 |
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- Wer: 0.4294 |
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- Cer: 0.0876 |
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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: 6 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 24 |
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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: 3000 |
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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 | Cer | |
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|:-------------:|:-------:|:----:|:---------------:|:------:|:------:| |
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| 5.755 | 2.1622 | 300 | 3.4394 | 1.0 | 1.0 | |
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| 1.5526 | 4.3243 | 600 | 0.7064 | 0.7488 | 0.1865 | |
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| 0.6682 | 6.4865 | 900 | 0.5412 | 0.6252 | 0.1383 | |
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| 0.4698 | 8.6486 | 1200 | 0.4891 | 0.5767 | 0.1271 | |
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| 0.3632 | 10.8108 | 1500 | 0.3958 | 0.5024 | 0.1004 | |
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| 0.2918 | 12.9730 | 1800 | 0.4565 | 0.5020 | 0.1055 | |
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| 0.2335 | 15.1351 | 2100 | 0.4298 | 0.4723 | 0.0981 | |
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| 0.1956 | 17.2973 | 2400 | 0.3805 | 0.4466 | 0.0888 | |
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| 0.1665 | 19.4595 | 2700 | 0.4039 | 0.4311 | 0.0889 | |
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| 0.1447 | 21.6216 | 3000 | 0.4124 | 0.4294 | 0.0876 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 1.18.3 |
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- Tokenizers 0.19.1 |
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