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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-large |
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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-large-sw-cv-100hr-v6 |
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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-large-sw-cv-100hr-v6 |
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This model is a fine-tuned version of [facebook/wav2vec2-large](https://huggingface.co/facebook/wav2vec2-large) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6098 |
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- Model Preparation Time: 0.0065 |
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- Wer: 0.3875 |
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- Cer: 0.1346 |
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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: 0.001 |
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- train_batch_size: 64 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.2 |
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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 | Cer | Validation Loss | Model Preparation Time | Wer | |
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|:-------------:|:-----:|:-----:|:------:|:---------------:|:----------------------:|:------:| |
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| 2.1201 | 1.0 | 1040 | 0.1472 | 0.6354 | 0.0059 | 0.5377 | |
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| 0.4194 | 2.0 | 2080 | 0.1104 | 0.4653 | 0.0059 | 0.4050 | |
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| 0.3266 | 3.0 | 3120 | 0.1087 | 0.3807 | 0.0059 | 0.3726 | |
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| 0.2997 | 4.0 | 4160 | 0.0944 | 0.3834 | 0.0059 | 0.3445 | |
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| 0.2984 | 5.0 | 5200 | 0.0979 | 0.4147 | 0.0059 | 0.3493 | |
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| 0.3072 | 6.0 | 6240 | 0.1020 | 0.4111 | 0.0059 | 0.3583 | |
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| 0.3265 | 7.0 | 7280 | 0.1147 | 0.4162 | 0.0059 | 0.3947 | |
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| 0.3477 | 8.0 | 8320 | 0.4503 | 0.0065 | 0.3979 | 0.1191 | |
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| 0.384 | 9.0 | 9360 | 0.5286 | 0.0065 | 0.4552 | 0.1442 | |
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| 0.4269 | 10.0 | 10400 | 0.5312 | 0.0065 | 0.4761 | 0.1471 | |
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| 1.5371 | 11.0 | 11440 | 4.5667 | 0.0065 | 0.9999 | 0.9827 | |
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| 4.5758 | 12.0 | 12480 | 4.5229 | 0.0065 | 0.9999 | 0.9827 | |
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| 4.5739 | 13.0 | 13520 | 4.5302 | 0.0065 | 0.9999 | 0.9827 | |
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| 4.5753 | 14.0 | 14560 | 4.5329 | 0.0065 | 0.9999 | 0.9827 | |
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| 4.5736 | 15.0 | 15600 | 4.5338 | 0.0065 | 0.9999 | 0.9827 | |
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| 4.5724 | 16.0 | 16640 | 4.5463 | 0.0065 | 0.9999 | 0.9827 | |
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| 4.5738 | 17.0 | 17680 | 4.5220 | 0.0065 | 0.9999 | 0.9827 | |
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### Framework versions |
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- Transformers 4.44.0 |
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- Pytorch 2.1.0+cu118 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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