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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: 0.3836 |
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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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| 23.2159 | 0.6 | 100 | 22.1148 | 1 | |
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| 18.1848 | 1.2 | 200 | 16.7223 | 1 | |
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| 9.7817 | 1.8 | 300 | 7.9404 | 1 | |
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| 4.5091 | 2.4 | 400 | 3.7900 | 1 | |
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| 3.4946 | 2.99 | 500 | 3.2953 | 1 | |
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| 3.3286 | 3.59 | 600 | 3.1827 | 1 | |
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| 3.2078 | 4.19 | 700 | 3.1068 | 1 | |
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| 3.1528 | 4.79 | 800 | 3.0573 | 1 | |
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| 3.0709 | 5.39 | 900 | 3.0196 | 1 | |
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| 3.0163 | 5.99 | 1000 | 2.9919 | 1 | |
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| 2.9789 | 6.59 | 1100 | 2.9504 | 1 | |
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| 2.9468 | 7.19 | 1200 | 2.9272 | 1 | |
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| 2.9389 | 7.78 | 1300 | 2.9129 | 1 | |
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| 2.9192 | 8.38 | 1400 | 2.9005 | 1 | |
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| 2.9069 | 8.98 | 1500 | 2.8861 | 1 | |
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| 2.9074 | 9.58 | 1600 | 2.8816 | 1 | |
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| 2.883 | 10.18 | 1700 | 2.8746 | 1 | |
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| 2.8746 | 10.78 | 1800 | 2.8718 | 1 | |
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| 2.8637 | 11.38 | 1900 | 2.8567 | 1 | |
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| 2.8613 | 11.98 | 2000 | 2.8570 | 1 | |
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| 2.8598 | 12.57 | 2100 | 2.8449 | 1 | |
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| 2.8357 | 13.17 | 2200 | 2.8393 | 1 | |
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| 2.8352 | 13.77 | 2300 | 2.8350 | 1 | |
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| 2.8178 | 14.37 | 2400 | 2.7879 | 1 | |
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| 2.5089 | 14.97 | 2500 | 2.3686 | 1 | |
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| 2.0826 | 15.57 | 2600 | 1.8915 | 1 | |
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| 1.6003 | 16.17 | 2700 | 1.3513 | 1 | |
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| 1.2925 | 16.77 | 2800 | 1.0568 | 1 | |
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| 1.0837 | 17.37 | 2900 | 0.8760 | 1 | |
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| 0.9333 | 17.96 | 3000 | 0.7588 | 1 | |
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| 0.8214 | 18.56 | 3100 | 0.6841 | 1 | |
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| 0.7302 | 19.16 | 3200 | 0.6099 | 1 | |
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| 0.6815 | 19.76 | 3300 | 0.5459 | 1 | |
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| 0.6548 | 20.36 | 3400 | 0.5087 | 1 | |
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| 0.569 | 20.96 | 3500 | 0.4853 | 1 | |
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| 0.5919 | 21.56 | 3600 | 0.4666 | 1 | |
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| 0.5306 | 22.16 | 3700 | 0.4508 | 1 | |
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| 0.5228 | 22.75 | 3800 | 0.4389 | 1 | |
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| 0.5263 | 23.35 | 3900 | 0.4287 | 1 | |
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| 0.4945 | 23.95 | 4000 | 0.4182 | 1 | |
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| 0.4809 | 24.55 | 4100 | 0.4122 | 1 | |
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| 0.4813 | 25.15 | 4200 | 0.4112 | 1 | |
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| 0.4664 | 25.75 | 4300 | 0.3972 | 1 | |
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| 0.455 | 26.35 | 4400 | 0.3950 | 1 | |
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| 0.4415 | 26.95 | 4500 | 0.3962 | 1 | |
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| 0.4399 | 27.54 | 4600 | 0.3930 | 1 | |
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| 0.4451 | 28.14 | 4700 | 0.3864 | 1 | |
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| 0.4343 | 28.74 | 4800 | 0.3867 | 1 | |
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| 0.4418 | 29.34 | 4900 | 0.3865 | 1 | |
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| 0.4223 | 29.94 | 5000 | 0.3836 | 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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