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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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metrics: |
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- accuracy |
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model-index: |
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- name: wav2vec2-base-finetuned-ic-slurp |
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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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# wav2vec2-base-finetuned-ic-slurp |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.1101 |
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- Accuracy: 0.7393 |
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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: 5e-05 |
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- train_batch_size: 24 |
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- eval_batch_size: 24 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 96 |
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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_ratio: 0.1 |
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- num_epochs: 50 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
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| 4.0345 | 1.0 | 527 | 3.9813 | 0.0673 | |
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| 3.5622 | 2.0 | 1055 | 3.4634 | 0.1867 | |
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| 2.7737 | 3.0 | 1582 | 2.7252 | 0.3638 | |
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| 2.1285 | 4.0 | 2110 | 2.1754 | 0.4827 | |
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| 1.6216 | 5.0 | 2637 | 1.8169 | 0.5701 | |
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| 1.1786 | 6.0 | 3165 | 1.5773 | 0.6347 | |
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| 0.8747 | 7.0 | 3692 | 1.5024 | 0.6568 | |
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| 0.7565 | 8.0 | 4220 | 1.5020 | 0.6694 | |
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| 0.5236 | 9.0 | 4747 | 1.5287 | 0.6799 | |
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| 0.4517 | 10.0 | 5275 | 1.5165 | 0.6879 | |
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| 0.364 | 11.0 | 5802 | 1.5159 | 0.6949 | |
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| 0.3221 | 12.0 | 6330 | 1.5217 | 0.6996 | |
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| 0.227 | 13.0 | 6857 | 1.5718 | 0.7075 | |
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| 0.1828 | 14.0 | 7385 | 1.6979 | 0.6901 | |
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| 0.1691 | 15.0 | 7912 | 1.6162 | 0.7093 | |
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| 0.1642 | 16.0 | 8440 | 1.6973 | 0.7048 | |
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| 0.1254 | 17.0 | 8967 | 1.7060 | 0.7100 | |
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| 0.1578 | 18.0 | 9495 | 1.7328 | 0.7063 | |
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| 0.1509 | 19.0 | 10022 | 1.7658 | 0.7073 | |
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| 0.1409 | 20.0 | 10550 | 1.7770 | 0.7052 | |
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| 0.1085 | 21.0 | 11077 | 1.8033 | 0.7074 | |
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| 0.106 | 22.0 | 11605 | 1.7000 | 0.7149 | |
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| 0.0764 | 23.0 | 12132 | 1.7943 | 0.7104 | |
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| 0.0671 | 24.0 | 12660 | 1.8323 | 0.7155 | |
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| 0.0768 | 25.0 | 13187 | 1.8486 | 0.7146 | |
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| 0.0741 | 26.0 | 13715 | 1.8227 | 0.7187 | |
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| 0.0731 | 27.0 | 14242 | 1.7824 | 0.7230 | |
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| 0.0935 | 28.0 | 14770 | 1.8987 | 0.7164 | |
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| 0.0829 | 29.0 | 15297 | 1.8774 | 0.7202 | |
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| 0.0588 | 30.0 | 15825 | 1.8820 | 0.7211 | |
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| 0.059 | 31.0 | 16352 | 1.9535 | 0.7246 | |
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| 0.0431 | 32.0 | 16880 | 1.9621 | 0.7237 | |
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| 0.0324 | 33.0 | 17407 | 2.0160 | 0.7256 | |
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| 0.0447 | 34.0 | 17935 | 1.9392 | 0.7262 | |
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| 0.025 | 35.0 | 18462 | 2.0095 | 0.7284 | |
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| 0.0522 | 36.0 | 18990 | 1.9994 | 0.7244 | |
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| 0.0482 | 37.0 | 19517 | 2.0566 | 0.7262 | |
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| 0.0203 | 38.0 | 20045 | 2.0287 | 0.7295 | |
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| 0.0221 | 39.0 | 20572 | 2.0634 | 0.7300 | |
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| 0.0444 | 40.0 | 21100 | 2.0593 | 0.7302 | |
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| 0.0348 | 41.0 | 21627 | 2.0712 | 0.7298 | |
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| 0.0154 | 42.0 | 22155 | 2.0429 | 0.7351 | |
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| 0.024 | 43.0 | 22682 | 2.0708 | 0.7352 | |
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| 0.0157 | 44.0 | 23210 | 2.0701 | 0.7368 | |
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| 0.0222 | 45.0 | 23737 | 2.0963 | 0.7338 | |
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| 0.0126 | 46.0 | 24265 | 2.1329 | 0.7340 | |
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| 0.0211 | 47.0 | 24792 | 2.1230 | 0.7370 | |
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| 0.0288 | 48.0 | 25320 | 2.1101 | 0.7393 | |
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| 0.0347 | 49.0 | 25847 | 2.1201 | 0.7375 | |
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| 0.0162 | 49.95 | 26350 | 2.1197 | 0.7381 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.2.0+cu121 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.2 |
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