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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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- wer |
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model-index: |
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- name: assis |
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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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# assis |
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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: 0.8484 |
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- Wer: 1 |
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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: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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: 3000 |
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- training_steps: 5000 |
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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 | Wer | |
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|:-------------:|:-----:|:----:|:---------------:|:---:| |
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| 22.3611 | 0.45 | 100 | 25.5854 | 1 | |
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| 20.8274 | 0.9 | 200 | 20.4977 | 1 | |
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| 12.1089 | 1.35 | 300 | 11.0220 | 1 | |
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| 5.043 | 1.81 | 400 | 4.3838 | 1 | |
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| 3.788 | 2.26 | 500 | 3.5831 | 1 | |
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| 3.445 | 2.71 | 600 | 3.4112 | 1 | |
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| 3.3042 | 3.16 | 700 | 3.3104 | 1 | |
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| 3.221 | 3.61 | 800 | 3.2255 | 1 | |
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| 3.1628 | 4.06 | 900 | 3.1618 | 1 | |
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| 3.0645 | 4.51 | 1000 | 3.1010 | 1 | |
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| 3.0913 | 4.97 | 1100 | 3.0624 | 1 | |
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| 3.0819 | 5.42 | 1200 | 3.0136 | 1 | |
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| 2.9502 | 5.87 | 1300 | 2.9883 | 1 | |
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| 2.9611 | 6.32 | 1400 | 2.9651 | 1 | |
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| 2.9287 | 6.77 | 1500 | 2.9474 | 1 | |
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| 2.9461 | 7.22 | 1600 | 2.9280 | 1 | |
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| 2.9176 | 7.67 | 1700 | 2.9148 | 1 | |
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| 2.8986 | 8.13 | 1800 | 2.9138 | 1 | |
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| 2.8896 | 8.58 | 1900 | 2.9050 | 1 | |
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| 2.8879 | 9.03 | 2000 | 2.9093 | 1 | |
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| 2.9085 | 9.48 | 2100 | 2.8998 | 1 | |
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| 2.876 | 9.93 | 2200 | 2.8807 | 1 | |
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| 2.8649 | 10.38 | 2300 | 2.8734 | 1 | |
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| 2.8653 | 10.84 | 2400 | 2.8681 | 1 | |
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| 2.8683 | 11.29 | 2500 | 2.8596 | 1 | |
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| 2.8452 | 11.74 | 2600 | 2.8667 | 1 | |
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| 2.8468 | 12.19 | 2700 | 2.8514 | 1 | |
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| 2.846 | 12.64 | 2800 | 2.8541 | 1 | |
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| 2.8415 | 13.09 | 2900 | 2.8493 | 1 | |
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| 2.8195 | 13.54 | 3000 | 2.8472 | 1 | |
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| 2.8103 | 14.0 | 3100 | 2.8244 | 1 | |
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| 2.6495 | 14.45 | 3200 | 2.5809 | 1 | |
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| 2.3126 | 14.9 | 3300 | 2.1612 | 1 | |
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| 1.92 | 15.35 | 3400 | 1.7312 | 1 | |
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| 1.5734 | 15.8 | 3500 | 1.4245 | 1 | |
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| 1.4081 | 16.25 | 3600 | 1.2659 | 1 | |
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| 1.2573 | 16.7 | 3700 | 1.1694 | 1 | |
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| 1.194 | 17.16 | 3800 | 1.0930 | 1 | |
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| 1.1053 | 17.61 | 3900 | 1.0393 | 1 | |
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| 1.072 | 18.06 | 4000 | 0.9792 | 1 | |
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| 1.0148 | 18.51 | 4100 | 0.9468 | 1 | |
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| 0.9995 | 18.96 | 4200 | 0.9228 | 1 | |
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| 0.9688 | 19.41 | 4300 | 0.9071 | 1 | |
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| 0.956 | 19.86 | 4400 | 0.8950 | 1 | |
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| 0.9565 | 20.32 | 4500 | 0.8632 | 1 | |
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| 0.9215 | 20.77 | 4600 | 0.8673 | 1 | |
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| 0.9006 | 21.22 | 4700 | 0.8647 | 1 | |
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| 0.8645 | 21.67 | 4800 | 0.8566 | 1 | |
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| 0.8768 | 22.12 | 4900 | 0.8527 | 1 | |
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| 0.8809 | 22.57 | 5000 | 0.8484 | 1 | |
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### Framework versions |
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- Transformers 4.28.0 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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