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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-xls-r-300m |
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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: mascir_fr_wav2vec_version1000 |
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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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# mascir_fr_wav2vec_version1000 |
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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 an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4441 |
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- Wer: 0.3622 |
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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: 0.0001 |
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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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- 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: 1000 |
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- num_epochs: 50 |
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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 | 2.0 | 250 | 4.6558 | 1.0 | |
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| 5.4653 | 4.0 | 500 | 3.1189 | 1.0 | |
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| 5.4653 | 6.0 | 750 | 1.3807 | 0.9344 | |
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| 1.6415 | 8.0 | 1000 | 0.6832 | 0.5689 | |
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| 1.6415 | 10.0 | 1250 | 0.4986 | 0.48 | |
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| 0.3065 | 12.0 | 1500 | 0.4968 | 0.4711 | |
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| 0.3065 | 14.0 | 1750 | 0.4470 | 0.4533 | |
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| 0.1441 | 16.0 | 2000 | 0.4832 | 0.4433 | |
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| 0.1441 | 18.0 | 2250 | 0.5433 | 0.45 | |
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| 0.0938 | 20.0 | 2500 | 0.4734 | 0.4344 | |
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| 0.0938 | 22.0 | 2750 | 0.4745 | 0.4111 | |
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| 0.0727 | 24.0 | 3000 | 0.4236 | 0.4044 | |
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| 0.0727 | 26.0 | 3250 | 0.4692 | 0.4133 | |
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| 0.0556 | 28.0 | 3500 | 0.4411 | 0.3967 | |
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| 0.0556 | 30.0 | 3750 | 0.4722 | 0.3822 | |
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| 0.0422 | 32.0 | 4000 | 0.4845 | 0.3978 | |
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| 0.0422 | 34.0 | 4250 | 0.4818 | 0.4 | |
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| 0.0325 | 36.0 | 4500 | 0.4638 | 0.3944 | |
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| 0.0325 | 38.0 | 4750 | 0.4737 | 0.38 | |
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| 0.0284 | 40.0 | 5000 | 0.4615 | 0.3822 | |
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| 0.0284 | 42.0 | 5250 | 0.4491 | 0.3722 | |
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| 0.0235 | 44.0 | 5500 | 0.4480 | 0.3744 | |
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| 0.0235 | 46.0 | 5750 | 0.4630 | 0.3711 | |
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| 0.0172 | 48.0 | 6000 | 0.4421 | 0.3644 | |
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| 0.0172 | 50.0 | 6250 | 0.4441 | 0.3622 | |
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### Framework versions |
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- Transformers 4.31.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.2 |
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- Tokenizers 0.13.3 |
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