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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-xls-r-300m |
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tags: |
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- generated_from_trainer |
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datasets: |
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- common_voice_15_0 |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-xls-r-300m-br |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: common_voice_15_0 |
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type: common_voice_15_0 |
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config: br |
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split: None |
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args: br |
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metrics: |
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- name: Wer |
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type: wer |
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value: 50.08524001794527 |
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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-br |
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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 common_voice_15_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8404 |
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- Wer: 50.0852 |
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- Cer: 17.4519 |
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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: 4e-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: 300 |
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- num_epochs: 40 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Cer | Validation Loss | Wer | |
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|:-------------:|:-----:|:-----:|:-------:|:---------------:|:-------:| |
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| 6.6871 | 1.09 | 500 | 100.0 | 3.2774 | 100.0 | |
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| 3.0612 | 2.18 | 1000 | 99.9339 | 2.7879 | 99.9910 | |
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| 1.7934 | 3.27 | 1500 | 29.4362 | 1.1762 | 80.5922 | |
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| 1.0914 | 4.36 | 2000 | 25.0591 | 0.9210 | 70.7941 | |
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| 0.8895 | 5.45 | 2500 | 23.6321 | 0.8364 | 67.1243 | |
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| 0.7831 | 6.54 | 3000 | 22.4169 | 0.7813 | 63.9480 | |
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| 0.697 | 7.63 | 3500 | 21.4625 | 0.7820 | 61.8214 | |
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| 0.6474 | 8.71 | 4000 | 20.7367 | 0.7471 | 59.4437 | |
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| 0.5969 | 9.8 | 4500 | 20.0072 | 0.7255 | 57.8914 | |
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| 0.5677 | 10.89 | 5000 | 20.0563 | 0.7440 | 57.5774 | |
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| 0.5286 | 11.98 | 5500 | 19.7483 | 0.7622 | 56.2494 | |
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| 0.5054 | 13.07 | 6000 | 19.1510 | 0.7318 | 55.1548 | |
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| 0.4831 | 14.16 | 6500 | 19.2096 | 0.7731 | 54.6882 | |
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| 0.4606 | 15.25 | 7000 | 19.0282 | 0.7457 | 54.4459 | |
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| 0.4432 | 16.34 | 7500 | 18.9923 | 0.7638 | 54.1319 | |
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| 0.4116 | 17.43 | 8000 | 18.6880 | 0.7576 | 53.3692 | |
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| 0.4099 | 18.52 | 8500 | 18.6653 | 0.7944 | 53.1359 | |
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| 0.3991 | 19.61 | 9000 | 18.7258 | 0.8229 | 52.9296 | |
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| 0.3796 | 20.7 | 9500 | 18.4555 | 0.8106 | 52.3194 | |
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| 0.3715 | 21.79 | 10000 | 18.1078 | 0.7611 | 51.8798 | |
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| 0.359 | 22.88 | 10500 | 18.4139 | 0.7921 | 52.2207 | |
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| 0.3384 | 23.97 | 11000 | 18.0624 | 0.8022 | 51.4850 | |
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| 0.3367 | 25.05 | 11500 | 0.7921 | 51.5209 | 18.0322 | |
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| 0.3295 | 26.14 | 12000 | 0.8354 | 51.4491 | 17.9811 | |
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| 0.3183 | 27.23 | 12500 | 0.8171 | 51.0991 | 17.8488 | |
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| 0.3135 | 28.32 | 13000 | 0.8094 | 50.9915 | 17.7354 | |
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| 0.309 | 29.41 | 13500 | 0.8632 | 50.8659 | 17.7978 | |
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| 0.2922 | 30.5 | 14000 | 0.8268 | 50.7672 | 17.6636 | |
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| 0.2987 | 31.59 | 14500 | 0.8108 | 50.2557 | 17.5918 | |
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| 0.2914 | 32.68 | 15000 | 0.8237 | 50.0224 | 17.4708 | |
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| 0.2893 | 33.77 | 15500 | 0.8450 | 50.1211 | 17.3877 | |
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| 0.2853 | 34.86 | 16000 | 0.8354 | 50.4800 | 17.5464 | |
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| 0.2791 | 35.95 | 16500 | 0.8424 | 50.1929 | 17.5257 | |
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| 0.2732 | 37.04 | 17000 | 0.8390 | 50.2826 | 17.5653 | |
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| 0.2691 | 38.13 | 17500 | 0.8420 | 50.1122 | 17.4671 | |
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| 0.2702 | 39.22 | 18000 | 0.8404 | 50.0852 | 17.4519 | |
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### Framework versions |
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- Transformers 4.39.1 |
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- Pytorch 2.0.1+cu117 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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