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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-base |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: cmb-20s_asr-scr_w2v2-base_001 |
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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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# cmb-20s_asr-scr_w2v2-base_001 |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4292 |
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- Per: 0.1270 |
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- Pcc: 0.6421 |
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- Ctc Loss: 0.3927 |
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- Mse Loss: 0.9759 |
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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: 1e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 1 |
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- seed: 1111 |
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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: 8928 |
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- training_steps: 89280 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Per | Pcc | Ctc Loss | Mse Loss | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|:--------:|:--------:| |
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| 11.2433 | 3.0 | 8928 | 4.4453 | 0.9956 | 0.6128 | 3.7641 | 0.9015 | |
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| 3.0401 | 6.0 | 17856 | 1.4595 | 0.1725 | 0.6569 | 0.6144 | 0.8126 | |
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| 1.1033 | 9.0 | 26784 | 1.2737 | 0.1429 | 0.6630 | 0.4640 | 0.8414 | |
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| 0.6225 | 12.0 | 35712 | 1.2199 | 0.1361 | 0.6559 | 0.4317 | 0.9022 | |
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| 0.1917 | 15.0 | 44640 | 1.1453 | 0.1328 | 0.6507 | 0.4158 | 0.9433 | |
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| -0.2369 | 18.0 | 53568 | 1.0993 | 0.1299 | 0.6454 | 0.4055 | 1.0059 | |
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| -0.6422 | 21.0 | 62496 | 1.0154 | 0.1288 | 0.6420 | 0.4013 | 1.0500 | |
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| -1.0425 | 24.0 | 71424 | 0.7199 | 0.1279 | 0.6421 | 0.3942 | 1.0017 | |
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| -1.3918 | 27.0 | 80352 | 0.3882 | 0.1274 | 0.6428 | 0.3945 | 0.9264 | |
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| -1.6077 | 30.0 | 89280 | 0.4292 | 0.1270 | 0.6421 | 0.3927 | 0.9759 | |
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### Framework versions |
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- Transformers 4.38.1 |
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- Pytorch 2.0.1 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.2 |
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