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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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model-index: |
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- name: '' |
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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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# |
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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 None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: inf |
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- Wer: 0.2172 |
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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: 7.5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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- seed: 42 |
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- gradient_accumulation_steps: 8 |
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- total_train_batch_size: 128 |
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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: 2000 |
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- num_epochs: 5.0 |
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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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| 2.9114 | 0.29 | 1000 | inf | 0.9997 | |
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| 1.2436 | 0.57 | 2000 | inf | 0.4310 | |
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| 1.0552 | 0.86 | 3000 | inf | 0.3144 | |
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| 1.0044 | 1.15 | 4000 | inf | 0.2814 | |
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| 0.9718 | 1.43 | 5000 | inf | 0.2658 | |
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| 0.9502 | 1.72 | 6000 | inf | 0.2566 | |
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| 0.9418 | 2.01 | 7000 | inf | 0.2476 | |
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| 0.9215 | 2.29 | 8000 | inf | 0.2420 | |
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| 0.9236 | 2.58 | 9000 | inf | 0.2388 | |
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| 0.9014 | 2.87 | 10000 | inf | 0.2354 | |
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| 0.8814 | 3.15 | 11000 | inf | 0.2312 | |
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| 0.8809 | 3.44 | 12000 | inf | 0.2285 | |
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| 0.8717 | 3.73 | 13000 | inf | 0.2263 | |
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| 0.8787 | 4.01 | 14000 | inf | 0.2218 | |
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| 0.8567 | 4.3 | 15000 | inf | 0.2193 | |
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| 0.8488 | 4.59 | 16000 | inf | 0.2187 | |
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| 0.8359 | 4.87 | 17000 | inf | 0.2172 | |
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### Framework versions |
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- Transformers 4.17.0.dev0 |
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- Pytorch 1.10.2+cu102 |
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- Datasets 1.18.3.dev0 |
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- Tokenizers 0.11.0 |
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