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wav2vecvanilla_ctc_zero_infinity_longertrain

Automatic Speech Recognition
Transformers
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Safetensors
wav2vec2
Generated from Trainer
Inference Endpoints
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  1. README.md +95 -0
  2. model.safetensors +1 -1
  3. runs/Apr13_02-47-21_0a3cd2114bd2/events.out.tfevents.1712976617.0a3cd2114bd2.1264.3 +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-base-960h
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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: wav2vecvanilla_ctc_zero_infinity_longertrain
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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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+ # wav2vecvanilla_ctc_zero_infinity_longertrain
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+
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+ This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on an unknown dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 1.1396
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+ - Wer: 0.2973
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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: 4
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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: 500
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+ - num_epochs: 15
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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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+ | 1.4721 | 0.43 | 100 | 1.0565 | 0.4014 |
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+ | 1.2574 | 0.85 | 200 | 0.9707 | 0.3704 |
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+ | 1.1397 | 1.28 | 300 | 0.9644 | 0.3609 |
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+ | 1.0939 | 1.71 | 400 | 0.9610 | 0.3637 |
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+ | 1.0874 | 2.14 | 500 | 0.9508 | 0.3581 |
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+ | 1.0573 | 2.56 | 600 | 0.8865 | 0.3518 |
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+ | 1.0386 | 2.99 | 700 | 1.0304 | 0.3493 |
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+ | 0.9792 | 3.42 | 800 | 0.8235 | 0.3523 |
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+ | 0.9789 | 3.85 | 900 | 0.8404 | 0.3388 |
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+ | 0.9095 | 4.27 | 1000 | 1.0925 | 0.3588 |
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+ | 0.8947 | 4.7 | 1100 | 1.0126 | 0.3357 |
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+ | 0.8571 | 5.13 | 1200 | 1.1404 | 0.3550 |
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+ | 0.8276 | 5.56 | 1300 | 0.8135 | 0.3294 |
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+ | 0.8631 | 5.98 | 1400 | 0.8342 | 0.3279 |
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+ | 0.8134 | 6.41 | 1500 | 0.8524 | 0.3177 |
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+ | 0.8027 | 6.84 | 1600 | 0.8182 | 0.3207 |
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+ | 0.7556 | 7.26 | 1700 | 0.8445 | 0.3185 |
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+ | 0.737 | 7.69 | 1800 | 0.8919 | 0.3197 |
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+ | 0.7398 | 8.12 | 1900 | 0.8115 | 0.3167 |
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+ | 0.7069 | 8.55 | 2000 | 0.8346 | 0.3174 |
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+ | 0.7206 | 8.97 | 2100 | 0.9714 | 0.3147 |
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+ | 0.6946 | 9.4 | 2200 | 0.8138 | 0.3124 |
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+ | 0.6752 | 9.83 | 2300 | 0.8366 | 0.3086 |
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+ | 0.7256 | 10.26 | 2400 | 0.8482 | 0.3044 |
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+ | 0.7063 | 10.68 | 2500 | 0.8997 | 0.3041 |
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+ | 0.6399 | 11.11 | 2600 | 0.8614 | 0.3045 |
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+ | 0.6268 | 11.54 | 2700 | 0.8564 | 0.3018 |
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+ | 0.6665 | 11.97 | 2800 | 0.8531 | 0.3006 |
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+ | 0.622 | 12.39 | 2900 | 0.8759 | 0.3007 |
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+ | 0.6568 | 12.82 | 3000 | 1.3093 | 0.3023 |
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+ | 0.6296 | 13.25 | 3100 | 1.1312 | 0.3002 |
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+ | 0.6448 | 13.68 | 3200 | 1.1779 | 0.2994 |
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+ | 0.6188 | 14.1 | 3300 | 1.1203 | 0.2989 |
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+ | 0.6216 | 14.53 | 3400 | 1.1421 | 0.2978 |
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+ | 0.6238 | 14.96 | 3500 | 1.1396 | 0.2973 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.38.2
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.18.0
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+ - Tokenizers 0.15.2
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