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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: wav2vec2-xlsr-fi-lm-1B |
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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-xlsr-fi-lm-1B |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-1b](https://huggingface.co/facebook/wav2vec2-xls-r-1b) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1853 |
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- Wer: 0.2205 |
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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: 4 |
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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: 10 |
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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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| 0.8158 | 0.67 | 400 | 0.4835 | 0.6310 | |
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| 0.5679 | 1.33 | 800 | 0.4806 | 0.5538 | |
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| 0.6055 | 2.0 | 1200 | 0.3888 | 0.5083 | |
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| 0.5353 | 2.67 | 1600 | 0.3258 | 0.4365 | |
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| 0.4883 | 3.33 | 2000 | 0.3313 | 0.4204 | |
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| 0.4513 | 4.0 | 2400 | 0.2924 | 0.3904 | |
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| 0.3753 | 4.67 | 2800 | 0.2593 | 0.3608 | |
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| 0.3478 | 5.33 | 3200 | 0.2832 | 0.3551 | |
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| 0.3796 | 6.0 | 3600 | 0.2495 | 0.3402 | |
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| 0.2556 | 6.67 | 4000 | 0.2342 | 0.3106 | |
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| 0.229 | 7.33 | 4400 | 0.2181 | 0.2812 | |
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| 0.205 | 8.0 | 4800 | 0.2041 | 0.2523 | |
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| 0.1654 | 8.67 | 5200 | 0.2015 | 0.2416 | |
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| 0.152 | 9.33 | 5600 | 0.1942 | 0.2294 | |
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| 0.1569 | 10.0 | 6000 | 0.1853 | 0.2205 | |
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### Framework versions |
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- Transformers 4.16.0.dev0 |
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- Pytorch 1.10.1+cu102 |
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- Datasets 1.17.1.dev0 |
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- Tokenizers 0.11.0 |
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