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--- |
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language: |
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- ta |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-large-xlsr-53 |
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tags: |
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- automatic-speech-recognition |
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- mozilla-foundation/common_voice_6_1 |
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- generated_from_trainer |
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datasets: |
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- common_voice_6_1 |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-common_voice-ta |
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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: MOZILLA-FOUNDATION/COMMON_VOICE_6_1 - TA |
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type: common_voice_6_1 |
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config: ta |
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split: test |
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args: 'Config: ta, Training split: train+validation, Eval split: test' |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.7095686384712659 |
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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-common_voice-ta |
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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 MOZILLA-FOUNDATION/COMMON_VOICE_6_1 - TA dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6563 |
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- Wer: 0.7096 |
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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: 15.0 |
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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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| No log | 0.84 | 100 | 4.3941 | 1.0 | |
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| No log | 1.69 | 200 | 3.2005 | 1.0 | |
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| No log | 2.53 | 300 | 2.7844 | 1.0145 | |
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| No log | 3.38 | 400 | 0.8691 | 1.0003 | |
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| 4.317 | 4.22 | 500 | 0.6846 | 0.8394 | |
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| 4.317 | 5.06 | 600 | 0.6270 | 0.7790 | |
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| 4.317 | 5.91 | 700 | 0.5935 | 0.7802 | |
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| 4.317 | 6.75 | 800 | 0.5701 | 0.7812 | |
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| 4.317 | 7.59 | 900 | 0.5649 | 0.7891 | |
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| 0.3656 | 8.44 | 1000 | 0.6092 | 0.8178 | |
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| 0.3656 | 9.28 | 1100 | 0.6093 | 0.7721 | |
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| 0.3656 | 10.13 | 1200 | 0.6154 | 0.7287 | |
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| 0.3656 | 10.97 | 1300 | 0.6284 | 0.7408 | |
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| 0.3656 | 11.81 | 1400 | 0.6343 | 0.7143 | |
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| 0.1681 | 12.66 | 1500 | 0.6523 | 0.7363 | |
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| 0.1681 | 13.5 | 1600 | 0.6543 | 0.7139 | |
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| 0.1681 | 14.35 | 1700 | 0.6599 | 0.7094 | |
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### Framework versions |
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- Transformers 4.38.0.dev0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.1 |
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