77 lines
2.3 KiB
Markdown
77 lines
2.3 KiB
Markdown
---
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license: apache-2.0
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tags:
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- generated_from_trainer
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datasets:
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- filipino_voice
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model-index:
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- name: filipino-wav2vec2-l-xls-r-300m-official
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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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# filipino-wav2vec2-l-xls-r-300m-official
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the filipino_voice dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.4672
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- Wer: 0.2922
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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: 8
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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: 16
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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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- 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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| 3.3671 | 2.09 | 400 | 0.5584 | 0.5987 |
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| 0.48 | 4.19 | 800 | 0.4244 | 0.4195 |
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| 0.2796 | 6.28 | 1200 | 0.3742 | 0.3765 |
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| 0.1916 | 8.38 | 1600 | 0.4291 | 0.3667 |
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| 0.1463 | 10.47 | 2000 | 0.3745 | 0.3415 |
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| 0.1165 | 12.57 | 2400 | 0.4472 | 0.3407 |
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| 0.0955 | 14.66 | 2800 | 0.4269 | 0.3290 |
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| 0.0823 | 16.75 | 3200 | 0.4608 | 0.3475 |
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| 0.0709 | 18.85 | 3600 | 0.4706 | 0.3281 |
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| 0.0603 | 20.94 | 4000 | 0.4380 | 0.3183 |
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| 0.0527 | 23.04 | 4400 | 0.4473 | 0.3067 |
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| 0.0449 | 25.13 | 4800 | 0.4550 | 0.3029 |
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| 0.041 | 27.23 | 5200 | 0.4671 | 0.3020 |
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| 0.0358 | 29.32 | 5600 | 0.4672 | 0.2922 |
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### Framework versions
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- Transformers 4.11.3
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- Pytorch 1.10.0+cu113
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- Datasets 1.18.3
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- Tokenizers 0.10.3
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