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wav2vec2-large-xls-r-300m

Automatic Speech Recognition
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wav2vec2
Generated from Trainer
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  1. README.md +97 -0
  2. model.safetensors +1 -1
  3. runs/Dec26_02-45-35_2f7c798edc1a/events.out.tfevents.1703559148.2f7c798edc1a.6021.0 +2 -2
README.md ADDED
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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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+ model-index:
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+ - name: wav2vec2-large-xls-r-300m
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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-large-xls-r-300m
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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 an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 3.6299
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+ - Cer: 69.5709
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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: 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: 100
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+ - num_epochs: 5
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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 | Cer |
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+ |:-------------:|:-----:|:----:|:---------------:|:-------:|
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+ | 56.9189 | 0.13 | 200 | 17.3335 | 100.0 |
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+ | 24.9477 | 0.26 | 400 | 5.2898 | 93.4002 |
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+ | 22.4883 | 0.39 | 600 | 5.1855 | 91.7503 |
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+ | 23.6577 | 0.52 | 800 | 5.5828 | 93.8097 |
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+ | 12.0508 | 0.64 | 1000 | 5.5876 | 92.9788 |
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+ | 6.9102 | 0.77 | 1200 | 5.2180 | 93.1153 |
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+ | 5.2937 | 0.9 | 1400 | 4.6411 | 93.6613 |
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+ | 4.6224 | 1.03 | 1600 | 4.7614 | 93.7088 |
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+ | 4.6148 | 1.16 | 1800 | 4.8569 | 93.0916 |
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+ | 4.6129 | 1.29 | 2000 | 4.6641 | 92.5693 |
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+ | 4.5837 | 1.42 | 2200 | 4.7341 | 93.5664 |
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+ | 4.5465 | 1.55 | 2400 | 4.7580 | 93.3646 |
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+ | 4.5042 | 1.68 | 2600 | 4.8342 | 93.4180 |
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+ | 4.4535 | 1.81 | 2800 | 4.8323 | 93.4952 |
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+ | 4.3942 | 1.93 | 3000 | 4.7891 | 92.1538 |
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+ | 4.347 | 2.06 | 3200 | 4.5461 | 92.4150 |
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+ | 4.3064 | 2.19 | 3400 | 4.7049 | 92.0114 |
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+ | 4.301 | 2.32 | 3600 | 4.6162 | 92.3438 |
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+ | 4.2107 | 2.45 | 3800 | 4.5264 | 92.3497 |
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+ | 4.1768 | 2.58 | 4000 | 4.4067 | 87.1090 |
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+ | 4.1395 | 2.71 | 4200 | 4.5684 | 90.6048 |
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+ | 4.0568 | 2.84 | 4400 | 4.4142 | 87.7856 |
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+ | 4.0007 | 2.97 | 4600 | 4.2861 | 87.7619 |
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+ | 3.9426 | 3.09 | 4800 | 4.2750 | 87.4236 |
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+ | 3.8207 | 3.22 | 5000 | 4.2217 | 84.2424 |
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+ | 3.7678 | 3.35 | 5200 | 4.1129 | 81.1324 |
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+ | 3.7522 | 3.48 | 5400 | 4.0891 | 83.2512 |
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+ | 3.6666 | 3.61 | 5600 | 4.0328 | 80.0107 |
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+ | 3.587 | 3.74 | 5800 | 4.0241 | 80.2837 |
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+ | 3.5184 | 3.87 | 6000 | 4.0116 | 81.8209 |
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+ | 3.449 | 4.0 | 6200 | 3.9031 | 76.4437 |
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+ | 3.3503 | 4.13 | 6400 | 3.8643 | 75.8680 |
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+ | 3.2541 | 4.26 | 6600 | 3.8508 | 72.4850 |
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+ | 3.1987 | 4.38 | 6800 | 3.8425 | 71.8203 |
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+ | 3.1435 | 4.51 | 7000 | 3.7289 | 71.6719 |
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+ | 3.0583 | 4.64 | 7200 | 3.6855 | 70.1703 |
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+ | 3.0443 | 4.77 | 7400 | 3.6365 | 69.6540 |
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+ | 3.0508 | 4.9 | 7600 | 3.6299 | 69.5709 |
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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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