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wav2vec2-xls-r-300m-br

Automatic Speech Recognition
Transformers
TensorBoard
Safetensors
Breton
wav2vec2
Generated from Trainer
Eval Results
Inference Endpoints
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  1. .ipynb_checkpoints/README-checkpoint.md +87 -0
  2. model.safetensors +1 -1
  3. runs/Jun02_20-39-22_gweltaz-NUC10i7FNK/events.out.tfevents.1717353679.gweltaz-NUC10i7FNK.3738.0 +2 -2
  4. runs/Jun03_13-04-10_gweltaz-NUC10i7FNK/events.out.tfevents.1717412768.gweltaz-NUC10i7FNK.2856.0 +3 -0
  5. training_args.bin +1 -1
.ipynb_checkpoints/README-checkpoint.md ADDED
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+ ---
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+ language:
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+ - br
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+ license: apache-2.0
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+ tags:
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+ - generated_from_trainer
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+ base_model: facebook/wav2vec2-xls-r-300m
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+ datasets:
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+ - mozilla-foundation/common_voice_15_0
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: wav2vec2-xls-r-300m-breton
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+ results: []
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+ ---
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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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+ # wav2vec2-xls-r-300m-breton
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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 [mozilla-foundation/common_voice_15_0]() dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.9939
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+ - Wer: 0.4680
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+ - Cer: 0.1711
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 6e-05
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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_ratio: 0.08
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+ - num_epochs: 50
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
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+ |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
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+ | 10.4347 | 2.56 | 250 | 3.7906 | 1.0 | 1.0 |
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+ | 3.2144 | 5.13 | 500 | 3.0622 | 1.0 | 1.0 |
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+ | 2.6193 | 7.69 | 750 | 1.6063 | 0.9122 | 0.4042 |
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+ | 1.3658 | 10.26 | 1000 | 1.0917 | 0.7061 | 0.2474 |
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+ | 0.9614 | 12.82 | 1250 | 0.9805 | 0.6384 | 0.2245 |
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+ | 0.7915 | 15.38 | 1500 | 0.9340 | 0.5989 | 0.2124 |
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+ | 0.6728 | 17.95 | 1750 | 0.9135 | 0.5735 | 0.2016 |
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+ | 0.5889 | 20.51 | 2000 | 0.9381 | 0.5443 | 0.1944 |
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+ | 0.5374 | 23.08 | 2250 | 0.9517 | 0.5372 | 0.1918 |
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+ | 0.4972 | 25.64 | 2500 | 0.9171 | 0.5134 | 0.1828 |
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+ | 0.4537 | 28.21 | 2750 | 0.9457 | 0.5043 | 0.1804 |
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+ | 0.4217 | 30.77 | 3000 | 0.9479 | 0.4957 | 0.1789 |
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+ | 0.4082 | 33.33 | 3250 | 0.9400 | 0.4906 | 0.1762 |
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+ | 0.4005 | 35.9 | 3500 | 0.9710 | 0.4881 | 0.1770 |
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+ | 0.3702 | 38.46 | 3750 | 0.9922 | 0.4792 | 0.1757 |
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+ | 0.3473 | 41.03 | 4000 | 0.9724 | 0.4760 | 0.1734 |
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+ | 0.3405 | 43.59 | 4250 | 0.9860 | 0.4726 | 0.1722 |
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+ | 0.325 | 46.15 | 4500 | 0.9888 | 0.4679 | 0.1705 |
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+ | 0.3193 | 48.72 | 4750 | 0.9939 | 0.4680 | 0.1711 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.35.2
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.16.0
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+ - Tokenizers 0.15.0
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