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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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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-timit-xls-r-300m-colab |
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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-timit-xls-r-300m-colab |
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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: 0.3293 |
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- Wer: 0.2879 |
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- Cer: 0.0927 |
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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 | Cer | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:| |
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| No log | 0.69 | 400 | 3.1501 | 1.0 | 0.9865 | |
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| 4.3829 | 1.38 | 800 | 2.9694 | 1.0 | 0.9865 | |
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| 2.6389 | 2.08 | 1200 | 0.6558 | 0.5876 | 0.1878 | |
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| 0.9293 | 2.77 | 1600 | 0.4232 | 0.4722 | 0.1462 | |
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| 0.5686 | 3.46 | 2000 | 0.3513 | 0.4118 | 0.1279 | |
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| 0.5686 | 4.15 | 2400 | 0.3246 | 0.3994 | 0.1227 | |
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| 0.4388 | 4.84 | 2800 | 0.3037 | 0.3716 | 0.1158 | |
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| 0.3431 | 5.54 | 3200 | 0.3055 | 0.3674 | 0.1158 | |
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| 0.3164 | 6.23 | 3600 | 0.2973 | 0.3589 | 0.1128 | |
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| 0.2678 | 6.92 | 4000 | 0.3053 | 0.3421 | 0.1080 | |
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| 0.2678 | 7.61 | 4400 | 0.3058 | 0.3435 | 0.1083 | |
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| 0.2376 | 8.3 | 4800 | 0.3144 | 0.3408 | 0.1094 | |
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| 0.2199 | 9.0 | 5200 | 0.3177 | 0.3371 | 0.1052 | |
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| 0.1988 | 9.69 | 5600 | 0.3123 | 0.3299 | 0.1057 | |
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| 0.1816 | 10.38 | 6000 | 0.2918 | 0.3282 | 0.1049 | |
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| 0.1816 | 11.07 | 6400 | 0.3195 | 0.3270 | 0.1049 | |
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| 0.1652 | 11.76 | 6800 | 0.3080 | 0.3280 | 0.1056 | |
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| 0.1576 | 12.46 | 7200 | 0.2859 | 0.3218 | 0.1031 | |
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| 0.1558 | 13.15 | 7600 | 0.3143 | 0.3179 | 0.1018 | |
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| 0.1411 | 13.84 | 8000 | 0.3354 | 0.3171 | 0.1045 | |
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| 0.1411 | 14.53 | 8400 | 0.3285 | 0.3149 | 0.1018 | |
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| 0.1381 | 15.22 | 8800 | 0.3048 | 0.3138 | 0.1010 | |
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| 0.1178 | 15.92 | 9200 | 0.3421 | 0.3140 | 0.1012 | |
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| 0.1182 | 16.61 | 9600 | 0.3258 | 0.3109 | 0.1001 | |
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| 0.1131 | 17.3 | 10000 | 0.3220 | 0.3120 | 0.1002 | |
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| 0.1131 | 17.99 | 10400 | 0.3156 | 0.3098 | 0.0991 | |
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| 0.1031 | 18.69 | 10800 | 0.3198 | 0.3062 | 0.0980 | |
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| 0.1023 | 19.38 | 11200 | 0.3227 | 0.3021 | 0.0972 | |
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| 0.0959 | 20.07 | 11600 | 0.3187 | 0.3025 | 0.0973 | |
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| 0.0881 | 20.76 | 12000 | 0.3177 | 0.3004 | 0.0965 | |
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| 0.0881 | 21.45 | 12400 | 0.3435 | 0.2976 | 0.0960 | |
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| 0.0919 | 22.15 | 12800 | 0.3142 | 0.2958 | 0.0954 | |
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| 0.0787 | 22.84 | 13200 | 0.3010 | 0.3000 | 0.0970 | |
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| 0.0794 | 23.53 | 13600 | 0.3528 | 0.3008 | 0.0973 | |
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| 0.0751 | 24.22 | 14000 | 0.3352 | 0.2954 | 0.0961 | |
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| 0.0751 | 24.91 | 14400 | 0.3314 | 0.2977 | 0.0963 | |
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| 0.0778 | 25.61 | 14800 | 0.3214 | 0.2955 | 0.0953 | |
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| 0.0711 | 26.3 | 15200 | 0.3277 | 0.2936 | 0.0944 | |
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| 0.0681 | 26.99 | 15600 | 0.3237 | 0.2915 | 0.0940 | |
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| 0.0682 | 27.68 | 16000 | 0.3284 | 0.2918 | 0.0943 | |
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| 0.0682 | 28.37 | 16400 | 0.3304 | 0.2904 | 0.0933 | |
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| 0.0731 | 29.07 | 16800 | 0.3307 | 0.2881 | 0.0927 | |
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| 0.0619 | 29.76 | 17200 | 0.3293 | 0.2879 | 0.0927 | |
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### Framework versions |
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- Transformers 4.32.0.dev0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 1.18.3 |
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- Tokenizers 0.13.3 |
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