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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 |
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model-index: |
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- name: wav2vec2-large-mn-pretrain-42h-100-epochs |
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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-large-mn-pretrain-42h-100-epochs |
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This model is a fine-tuned version of [bayartsogt/wav2vec2-large-mn-pretrain-42h](https://huggingface.co/bayartsogt/wav2vec2-large-mn-pretrain-42h) on the common_voice dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 6.4172 |
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- Wer: 1.0 |
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- Cer: 0.9841 |
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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: 2e-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: 500 |
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- training_steps: 10000 |
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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 | Cer | |
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|:-------------:|:-----:|:-----:|:---------------:|:---:|:------:| |
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| 7.6418 | 1.59 | 400 | 6.4239 | 1.0 | 0.9841 | |
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| 5.5936 | 3.19 | 800 | 6.4154 | 1.0 | 0.9841 | |
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| 5.5208 | 4.78 | 1200 | 6.5248 | 1.0 | 0.9841 | |
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| 5.4869 | 6.37 | 1600 | 6.3805 | 1.0 | 0.9841 | |
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| 5.4757 | 7.97 | 2000 | 6.3988 | 1.0 | 0.9841 | |
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| 5.4624 | 9.56 | 2400 | 6.4058 | 1.0 | 0.9841 | |
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| 5.517 | 11.16 | 2800 | 6.3991 | 1.0 | 0.9841 | |
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| 5.4821 | 12.75 | 3200 | 6.4066 | 1.0 | 0.9841 | |
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| 5.487 | 14.34 | 3600 | 6.4281 | 1.0 | 0.9841 | |
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| 5.4786 | 15.93 | 4000 | 6.4174 | 1.0 | 0.9841 | |
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| 5.5017 | 17.53 | 4400 | 6.4338 | 1.0 | 0.9841 | |
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| 5.4967 | 19.12 | 4800 | 6.4653 | 1.0 | 0.9841 | |
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| 5.4619 | 20.72 | 5200 | 6.4499 | 1.0 | 0.9841 | |
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| 5.4883 | 22.31 | 5600 | 6.4345 | 1.0 | 0.9841 | |
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| 5.4899 | 23.9 | 6000 | 6.4224 | 1.0 | 0.9841 | |
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| 5.493 | 25.5 | 6400 | 6.4374 | 1.0 | 0.9841 | |
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| 5.4549 | 27.09 | 6800 | 6.4320 | 1.0 | 0.9841 | |
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| 5.4531 | 28.68 | 7200 | 6.4137 | 1.0 | 0.9841 | |
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| 5.4738 | 30.28 | 7600 | 6.4155 | 1.0 | 0.9841 | |
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| 5.4309 | 31.87 | 8000 | 6.4193 | 1.0 | 0.9841 | |
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| 5.4669 | 33.47 | 8400 | 6.4109 | 1.0 | 0.9841 | |
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| 5.47 | 35.06 | 8800 | 6.4111 | 1.0 | 0.9841 | |
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| 5.4623 | 36.65 | 9200 | 6.4102 | 1.0 | 0.9841 | |
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| 5.4583 | 38.25 | 9600 | 6.4150 | 1.0 | 0.9841 | |
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| 5.4551 | 39.84 | 10000 | 6.4172 | 1.0 | 0.9841 | |
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### Framework versions |
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- Transformers 4.20.1 |
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- Pytorch 1.11.0 |
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- Datasets 2.1.0 |
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- Tokenizers 0.12.1 |
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