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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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model-index: |
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- name: wav2vec2-multiple-medical-2-1 |
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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-multiple-medical-2-1 |
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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: 0.2340 |
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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: 2 |
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- eval_batch_size: 2 |
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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_ratio: 0.1 |
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- num_epochs: 30 |
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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 | |
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|:-------------:|:-----:|:-----:|:---------------:| |
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| 5.7848 | 0.56 | 1500 | 4.7981 | |
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| 3.4426 | 1.12 | 3000 | 3.3244 | |
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| 3.1079 | 1.68 | 4500 | 3.0999 | |
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| 3.0034 | 2.24 | 6000 | 2.9647 | |
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| 2.0403 | 2.8 | 7500 | 1.5829 | |
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| 1.2797 | 3.36 | 9000 | 0.9095 | |
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| 1.052 | 3.92 | 10500 | 0.6498 | |
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| 0.8326 | 4.48 | 12000 | 0.5418 | |
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| 0.7443 | 5.04 | 13500 | 0.4615 | |
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| 0.6949 | 5.6 | 15000 | 0.4191 | |
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| 0.6096 | 6.16 | 16500 | 0.3817 | |
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| 0.5699 | 6.72 | 18000 | 0.3545 | |
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| 0.5718 | 7.28 | 19500 | 0.3439 | |
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| 0.5159 | 7.84 | 21000 | 0.3243 | |
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| 0.4808 | 8.4 | 22500 | 0.3112 | |
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| 0.4979 | 8.96 | 24000 | 0.2975 | |
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| 0.4271 | 9.52 | 25500 | 0.2948 | |
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| 0.4364 | 10.08 | 27000 | 0.2818 | |
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| 0.4205 | 10.64 | 28500 | 0.2770 | |
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| 0.418 | 11.2 | 30000 | 0.2747 | |
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| 0.3915 | 11.76 | 31500 | 0.2695 | |
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| 0.4121 | 12.32 | 33000 | 0.2596 | |
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| 0.4057 | 12.88 | 34500 | 0.2627 | |
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| 0.363 | 13.44 | 36000 | 0.2617 | |
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| 0.3767 | 14.0 | 37500 | 0.2567 | |
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| 0.3804 | 14.56 | 39000 | 0.2512 | |
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| 0.3537 | 15.12 | 40500 | 0.2505 | |
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| 0.3195 | 15.68 | 42000 | 0.2508 | |
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| 0.311 | 16.24 | 43500 | 0.2523 | |
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| 0.3089 | 16.8 | 45000 | 0.2462 | |
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| 0.3121 | 17.36 | 46500 | 0.2463 | |
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| 0.3549 | 17.92 | 48000 | 0.2479 | |
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| 0.3111 | 18.48 | 49500 | 0.2422 | |
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| 0.3228 | 19.04 | 51000 | 0.2414 | |
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| 0.2936 | 19.6 | 52500 | 0.2415 | |
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| 0.28 | 20.16 | 54000 | 0.2411 | |
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| 0.3174 | 20.72 | 55500 | 0.2354 | |
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| 0.2735 | 21.28 | 57000 | 0.2335 | |
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| 0.3498 | 21.84 | 58500 | 0.2352 | |
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| 0.2958 | 22.4 | 60000 | 0.2341 | |
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| 0.3009 | 22.96 | 61500 | 0.2328 | |
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| 0.2869 | 23.52 | 63000 | 0.2352 | |
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| 0.2644 | 24.08 | 64500 | 0.2343 | |
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| 0.2692 | 24.64 | 66000 | 0.2346 | |
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| 0.3376 | 25.2 | 67500 | 0.2339 | |
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| 0.2522 | 25.76 | 69000 | 0.2340 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.13.3 |
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