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Thanapon1998
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firstcolab3

Automatic Speech Recognition
Transformers
PyTorch
TensorBoard
wav2vec2
Generated from Trainer
Eval Results
Inference Endpoints
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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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+ datasets:
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+ - common_voice_11_0
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: firstcolab3
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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_11_0
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+ type: common_voice_11_0
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+ config: th
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+ split: train+validation
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+ args: th
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 0.6226224783861671
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+ ---
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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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+
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+ # firstcolab3
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+
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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_11_0 dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.2756
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+ - Wer: 0.6226
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+ - Cer: 0.0535
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 32
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+ - eval_batch_size: 16
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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: 500
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+ - num_epochs: 20
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
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+ |:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
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+ | 7.187 | 0.75 | 1000 | 3.7705 | 1.0 | 1.0 |
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+ | 2.0277 | 1.5 | 2000 | 0.6139 | 0.9202 | 0.1545 |
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+ | 0.8368 | 2.24 | 3000 | 0.4351 | 0.8589 | 0.1147 |
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+ | 0.6772 | 2.99 | 4000 | 0.3762 | 0.8200 | 0.0990 |
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+ | 0.5702 | 3.74 | 5000 | 0.3434 | 0.7889 | 0.0891 |
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+ | 0.5205 | 4.49 | 6000 | 0.3427 | 0.7726 | 0.0855 |
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+ | 0.4773 | 5.24 | 7000 | 0.3073 | 0.7408 | 0.0767 |
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+ | 0.4389 | 5.98 | 8000 | 0.2969 | 0.7421 | 0.0759 |
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+ | 0.4069 | 6.73 | 9000 | 0.2884 | 0.7134 | 0.0711 |
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+ | 0.3858 | 7.48 | 10000 | 0.2952 | 0.7066 | 0.0699 |
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+ | 0.36 | 8.23 | 11000 | 0.2846 | 0.6902 | 0.0662 |
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+ | 0.3517 | 8.98 | 12000 | 0.2729 | 0.6756 | 0.0638 |
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+ | 0.3265 | 9.72 | 13000 | 0.2844 | 0.6756 | 0.0645 |
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+ | 0.3127 | 10.47 | 14000 | 0.2769 | 0.6803 | 0.0640 |
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+ | 0.3016 | 11.22 | 15000 | 0.2772 | 0.6566 | 0.0618 |
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+ | 0.2855 | 11.97 | 16000 | 0.2791 | 0.6540 | 0.0598 |
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+ | 0.2699 | 12.72 | 17000 | 0.2714 | 0.6455 | 0.0589 |
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+ | 0.264 | 13.46 | 18000 | 0.2782 | 0.6472 | 0.0588 |
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+ | 0.2518 | 14.21 | 19000 | 0.2693 | 0.6398 | 0.0578 |
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+ | 0.2498 | 14.96 | 20000 | 0.2761 | 0.6300 | 0.0561 |
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+ | 0.2426 | 15.71 | 21000 | 0.2796 | 0.6366 | 0.0561 |
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+ | 0.2271 | 16.45 | 22000 | 0.2804 | 0.6336 | 0.0554 |
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+ | 0.2271 | 17.2 | 23000 | 0.2758 | 0.6347 | 0.0552 |
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+ | 0.22 | 17.95 | 24000 | 0.2785 | 0.6279 | 0.0544 |
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+ | 0.2143 | 18.7 | 25000 | 0.2783 | 0.6246 | 0.0538 |
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+ | 0.2134 | 19.45 | 26000 | 0.2756 | 0.6226 | 0.0535 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.24.0
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+ - Pytorch 1.12.1+cu113
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+ - Datasets 2.7.1
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+ - Tokenizers 0.13.2