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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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metrics: |
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- accuracy |
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model-index: |
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- name: wav2vec2-xls-r-300m-intent-classification-ori |
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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-xls-r-300m-intent-classification-ori |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.3107 |
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- Accuracy: 0.625 |
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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: 3e-05 |
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- train_batch_size: 2 |
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- eval_batch_size: 2 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 8 |
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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: 45 |
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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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| 2.1982 | 1.0 | 14 | 2.1951 | 0.0625 | |
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| 2.2021 | 2.0 | 28 | 2.1847 | 0.1458 | |
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| 2.1819 | 3.0 | 42 | 2.1661 | 0.3333 | |
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| 2.1789 | 4.0 | 56 | 2.1413 | 0.3333 | |
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| 2.164 | 5.0 | 70 | 2.1183 | 0.3333 | |
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| 2.1484 | 6.0 | 84 | 2.0974 | 0.3333 | |
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| 2.1199 | 7.0 | 98 | 2.0939 | 0.3333 | |
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| 2.1343 | 8.0 | 112 | 2.0829 | 0.3333 | |
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| 2.1397 | 9.0 | 126 | 2.0654 | 0.3333 | |
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| 2.1045 | 10.0 | 140 | 2.0553 | 0.3333 | |
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| 2.1083 | 11.0 | 154 | 2.0255 | 0.3333 | |
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| 2.0914 | 12.0 | 168 | 2.0065 | 0.3333 | |
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| 2.0434 | 13.0 | 182 | 1.9696 | 0.3333 | |
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| 2.0687 | 14.0 | 196 | 1.9231 | 0.4167 | |
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| 2.0237 | 15.0 | 210 | 1.8679 | 0.4167 | |
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| 1.9562 | 16.0 | 224 | 1.8184 | 0.4167 | |
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| 2.0361 | 17.0 | 238 | 1.8803 | 0.3958 | |
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| 1.888 | 18.0 | 252 | 1.7802 | 0.4167 | |
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| 1.899 | 19.0 | 266 | 1.7662 | 0.4167 | |
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| 1.8959 | 20.0 | 280 | 1.7076 | 0.4167 | |
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| 1.8368 | 21.0 | 294 | 1.6566 | 0.4375 | |
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| 1.7358 | 22.0 | 308 | 1.6283 | 0.5 | |
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| 1.7877 | 23.0 | 322 | 1.6411 | 0.4583 | |
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| 1.7311 | 24.0 | 336 | 1.5525 | 0.5208 | |
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| 1.7079 | 25.0 | 350 | 1.5163 | 0.5 | |
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| 1.6496 | 26.0 | 364 | 1.5458 | 0.5 | |
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| 1.6374 | 27.0 | 378 | 1.5211 | 0.5 | |
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| 1.6048 | 28.0 | 392 | 1.4533 | 0.5417 | |
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| 1.5927 | 29.0 | 406 | 1.4319 | 0.5 | |
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| 1.4987 | 30.0 | 420 | 1.4579 | 0.5208 | |
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| 1.5745 | 31.0 | 434 | 1.4167 | 0.6042 | |
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| 1.4632 | 32.0 | 448 | 1.4471 | 0.5417 | |
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| 1.4686 | 33.0 | 462 | 1.4116 | 0.5625 | |
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| 1.5368 | 34.0 | 476 | 1.3872 | 0.6042 | |
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| 1.4327 | 35.0 | 490 | 1.3491 | 0.5833 | |
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| 1.3978 | 36.0 | 504 | 1.3325 | 0.5833 | |
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| 1.4509 | 37.0 | 518 | 1.3236 | 0.6042 | |
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| 1.3881 | 38.0 | 532 | 1.3426 | 0.5833 | |
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| 1.39 | 39.0 | 546 | 1.3137 | 0.6042 | |
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| 1.4153 | 40.0 | 560 | 1.3123 | 0.625 | |
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| 1.3635 | 41.0 | 574 | 1.3224 | 0.6042 | |
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| 1.403 | 42.0 | 588 | 1.3111 | 0.6042 | |
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| 1.3763 | 43.0 | 602 | 1.3197 | 0.5833 | |
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| 1.3539 | 44.0 | 616 | 1.3077 | 0.6042 | |
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| 1.306 | 45.0 | 630 | 1.3107 | 0.625 | |
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### Framework versions |
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- Transformers 4.20.1 |
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- Pytorch 1.11.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.12.1 |
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