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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: torgo_xlsr_finetune-M04-2 |
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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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# torgo_xlsr_finetune-M04-2 |
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.2407 |
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- Wer: 1.2835 |
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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: 0.0001 |
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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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- 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: 1000 |
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- num_epochs: 30 |
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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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| 22.4872 | 0.88 | 500 | 3.2706 | 1.0 | |
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| 3.361 | 1.75 | 1000 | 2.8365 | 1.0 | |
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| 2.8532 | 2.63 | 1500 | 2.7444 | 1.0 | |
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| 2.5391 | 3.5 | 2000 | 2.1105 | 1.0824 | |
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| 1.6217 | 4.38 | 2500 | 1.7736 | 1.6424 | |
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| 1.1107 | 5.25 | 3000 | 1.5937 | 1.4918 | |
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| 0.8277 | 6.13 | 3500 | 1.5655 | 1.4729 | |
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| 0.6872 | 7.01 | 4000 | 1.6192 | 1.4671 | |
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| 0.5597 | 7.88 | 4500 | 1.6735 | 1.4176 | |
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| 0.4942 | 8.76 | 5000 | 1.5915 | 1.3847 | |
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| 0.4447 | 9.63 | 5500 | 1.8509 | 1.4506 | |
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| 0.3967 | 10.51 | 6000 | 1.7833 | 1.3929 | |
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| 0.3596 | 11.38 | 6500 | 2.0147 | 1.3776 | |
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| 0.3409 | 12.26 | 7000 | 1.8649 | 1.4 | |
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| 0.3169 | 13.13 | 7500 | 1.8252 | 1.3541 | |
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| 0.2962 | 14.01 | 8000 | 2.1108 | 1.3906 | |
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| 0.2934 | 14.89 | 8500 | 1.8004 | 1.3188 | |
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| 0.2564 | 15.76 | 9000 | 1.8681 | 1.3659 | |
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| 0.2447 | 16.64 | 9500 | 1.9341 | 1.3318 | |
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| 0.2248 | 17.51 | 10000 | 2.0251 | 1.3259 | |
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| 0.2234 | 18.39 | 10500 | 1.9982 | 1.2988 | |
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| 0.1955 | 19.26 | 11000 | 2.0277 | 1.3024 | |
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| 0.1882 | 20.14 | 11500 | 2.0001 | 1.2882 | |
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| 0.2022 | 21.02 | 12000 | 1.9842 | 1.2988 | |
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| 0.163 | 21.89 | 12500 | 1.9931 | 1.32 | |
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| 0.1732 | 22.77 | 13000 | 2.0577 | 1.2659 | |
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| 0.1522 | 23.64 | 13500 | 2.0511 | 1.2812 | |
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| 0.1367 | 24.52 | 14000 | 2.0308 | 1.2671 | |
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| 0.1393 | 25.39 | 14500 | 2.2392 | 1.2788 | |
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| 0.1407 | 26.27 | 15000 | 2.1329 | 1.2824 | |
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| 0.1244 | 27.15 | 15500 | 2.0721 | 1.2694 | |
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| 0.116 | 28.02 | 16000 | 2.1656 | 1.2824 | |
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| 0.125 | 28.9 | 16500 | 2.2338 | 1.2882 | |
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| 0.1063 | 29.77 | 17000 | 2.2407 | 1.2835 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 1.18.3 |
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- Tokenizers 0.13.2 |
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