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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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<!-- 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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# wav2vecvanilla_ctc_zero_infinity_longertrain |
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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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## 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: 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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### Training results |
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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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### Framework versions |
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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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