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--- |
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license: apache-2.0 |
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tags: |
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- generated_from_trainer |
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base_model: facebook/wav2vec2-large-xlsr-53 |
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datasets: |
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- common_voice_17_0 |
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metrics: |
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- wer |
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model-index: |
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- name: xlsr-am-adap-phon |
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results: |
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- task: |
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type: automatic-speech-recognition |
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name: Automatic Speech Recognition |
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dataset: |
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name: common_voice_17_0 |
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type: common_voice_17_0 |
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config: am |
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split: validation |
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args: am |
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metrics: |
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- type: wer |
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value: 0.9302421009437833 |
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name: Wer |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/badr-nlp/xlsr-continual-finetuning-amharic/runs/4961bdc2) |
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# xlsr-am-adap-phon |
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice_17_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.5869 |
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- Wer: 0.9302 |
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- Cer: 0.4393 |
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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: 500 |
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- num_epochs: 100 |
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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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| 6.6235 | 6.8966 | 100 | 6.3103 | 1.0 | 1.0 | |
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| 4.227 | 13.7931 | 200 | 4.2662 | 1.0 | 1.0 | |
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| 4.1461 | 20.6897 | 300 | 4.1543 | 1.0 | 0.9966 | |
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| 4.146 | 27.5862 | 400 | 4.1716 | 1.0 | 0.9859 | |
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| 4.105 | 34.4828 | 500 | 4.1391 | 1.0 | 0.9740 | |
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| 3.5688 | 41.3793 | 600 | 3.6625 | 1.0 | 0.9749 | |
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| 1.5705 | 48.2759 | 700 | 2.2315 | 1.0029 | 0.5187 | |
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| 0.6683 | 55.1724 | 800 | 2.2517 | 0.9684 | 0.4595 | |
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| 0.577 | 62.0690 | 900 | 2.2995 | 0.9528 | 0.4413 | |
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| 0.3109 | 68.9655 | 1000 | 2.4239 | 0.9397 | 0.4575 | |
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| 0.2803 | 75.8621 | 1100 | 2.4491 | 0.9508 | 0.4474 | |
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| 0.2136 | 82.7586 | 1200 | 2.4916 | 0.9179 | 0.4323 | |
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| 0.3282 | 89.6552 | 1300 | 2.5652 | 0.9302 | 0.4401 | |
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| 0.2118 | 96.5517 | 1400 | 2.5869 | 0.9302 | 0.4393 | |
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### Framework versions |
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- Transformers 4.42.0.dev0 |
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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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