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--- |
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base_model: ylacombe/w2v-bert-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_16_0 |
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metrics: |
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- wer |
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model-index: |
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- name: w2v-bert-2.0-mongolian-colab-CV16.0 |
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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_16_0 |
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type: common_voice_16_0 |
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config: mn |
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split: test |
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args: mn |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.3251033282575593 |
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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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# w2v-bert-2.0-mongolian-colab-CV16.0 |
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This model is a fine-tuned version of [ylacombe/w2v-bert-2.0](https://huggingface.co/ylacombe/w2v-bert-2.0) on the common_voice_16_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5032 |
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- Wer: 0.3251 |
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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: 5e-05 |
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- train_batch_size: 16 |
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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: 32 |
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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: 10 |
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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 | |
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|:-------------:|:-----:|:----:|:---------------:|:------:| |
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| 3.7516 | 0.79 | 100 | 2.4041 | 1.0089 | |
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| 1.0185 | 1.58 | 200 | 0.7642 | 0.6153 | |
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| 0.5366 | 2.37 | 300 | 0.6518 | 0.5328 | |
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| 0.4153 | 3.16 | 400 | 0.6116 | 0.4811 | |
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| 0.353 | 3.95 | 500 | 0.6357 | 0.4806 | |
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| 0.2876 | 4.74 | 600 | 0.6213 | 0.4434 | |
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| 0.2389 | 5.53 | 700 | 0.5103 | 0.4243 | |
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| 0.1735 | 6.32 | 800 | 0.5079 | 0.3753 | |
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| 0.1419 | 7.11 | 900 | 0.5264 | 0.3638 | |
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| 0.1031 | 7.91 | 1000 | 0.5454 | 0.3466 | |
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| 0.0743 | 8.7 | 1100 | 0.5286 | 0.3337 | |
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| 0.054 | 9.49 | 1200 | 0.5032 | 0.3251 | |
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### Framework versions |
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- Transformers 4.37.0.dev0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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