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wav2vec2-demo-F01-2

Automatic Speech Recognition
Transformers
PyTorch
wav2vec2
generated_from_trainer
Inference Endpoints
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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-demo-F01-2
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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-demo-F01-2
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+
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+ This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.6361
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+ - Wer: 0.9025
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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: 1000
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+ - num_epochs: 30
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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 |
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+ |:-------------:|:-----:|:-----:|:---------------:|:------:|
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+ | 23.7408 | 0.81 | 500 | 3.3782 | 1.0 |
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+ | 3.348 | 1.62 | 1000 | 2.9501 | 1.0 |
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+ | 2.8539 | 2.44 | 1500 | 2.6975 | 1.0 |
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+ | 2.311 | 3.25 | 2000 | 1.7770 | 1.3175 |
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+ | 1.5102 | 4.06 | 2500 | 1.3481 | 1.3515 |
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+ | 1.0616 | 4.87 | 3000 | 1.4306 | 1.2313 |
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+ | 0.8493 | 5.68 | 3500 | 1.2261 | 1.1701 |
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+ | 0.7058 | 6.49 | 4000 | 1.2132 | 1.1111 |
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+ | 0.6129 | 7.31 | 4500 | 1.4230 | 1.1429 |
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+ | 0.5513 | 8.12 | 5000 | 1.2003 | 1.0499 |
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+ | 0.4957 | 8.93 | 5500 | 1.5534 | 1.1043 |
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+ | 0.4456 | 9.74 | 6000 | 1.2315 | 1.0658 |
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+ | 0.4101 | 10.55 | 6500 | 1.1621 | 1.0680 |
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+ | 0.3776 | 11.36 | 7000 | 1.4302 | 1.0385 |
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+ | 0.3318 | 12.18 | 7500 | 1.3488 | 0.9977 |
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+ | 0.3189 | 12.99 | 8000 | 1.4050 | 1.0295 |
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+ | 0.3103 | 13.8 | 8500 | 1.4535 | 1.0385 |
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+ | 0.2791 | 14.61 | 9000 | 1.3318 | 1.0181 |
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+ | 0.2681 | 15.42 | 9500 | 1.5199 | 0.9909 |
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+ | 0.2352 | 16.23 | 10000 | 1.5019 | 1.0023 |
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+ | 0.235 | 17.05 | 10500 | 1.7984 | 0.9955 |
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+ | 0.2319 | 17.86 | 11000 | 1.3399 | 0.9705 |
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+ | 0.221 | 18.67 | 11500 | 1.8316 | 0.9342 |
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+ | 0.2154 | 19.48 | 12000 | 1.6837 | 0.9637 |
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+ | 0.1911 | 20.29 | 12500 | 1.6999 | 0.9388 |
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+ | 0.1754 | 21.1 | 13000 | 1.4801 | 0.9274 |
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+ | 0.1776 | 21.92 | 13500 | 1.7954 | 0.9206 |
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+ | 0.1616 | 22.73 | 14000 | 1.7891 | 0.9320 |
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+ | 0.1579 | 23.54 | 14500 | 1.5692 | 0.9116 |
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+ | 0.173 | 24.35 | 15000 | 1.4928 | 0.9048 |
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+ | 0.1561 | 25.16 | 15500 | 1.6492 | 0.9116 |
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+ | 0.1542 | 25.97 | 16000 | 1.7356 | 0.9048 |
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+ | 0.131 | 26.79 | 16500 | 1.7785 | 0.9048 |
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+ | 0.1295 | 27.6 | 17000 | 1.6532 | 0.9116 |
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+ | 0.1374 | 28.41 | 17500 | 1.6760 | 0.9093 |
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+ | 0.1186 | 29.22 | 18000 | 1.6361 | 0.9025 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.23.1
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+ - Pytorch 1.12.1+cu113
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+ - Datasets 1.18.3
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+ - Tokenizers 0.13.2