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--- |
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license: mit |
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base_model: facebook/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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- ml-superb-subset |
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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-ml-superb-xty |
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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: ml-superb-subset |
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type: ml-superb-subset |
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config: xty |
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split: test |
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args: xty |
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metrics: |
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- name: Wer |
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type: wer |
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value: 1.3984915147705845 |
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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-ml-superb-xty |
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This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the ml-superb-subset dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 2.3981 |
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- Wer: 1.3985 |
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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: 1e-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: 30 |
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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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| 3.5467 | 0.8219 | 30 | 2.8636 | 1.0 | |
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| 2.4639 | 1.6438 | 60 | 2.5298 | 1.0094 | |
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| 2.38 | 2.4658 | 90 | 2.4983 | 1.1263 | |
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| 2.2725 | 3.2877 | 120 | 2.4866 | 1.2319 | |
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| 2.2608 | 4.1096 | 150 | 2.5116 | 1.5405 | |
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| 2.2222 | 4.9315 | 180 | 2.4588 | 1.3300 | |
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| 2.2609 | 5.7534 | 210 | 2.4448 | 1.3451 | |
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| 2.1665 | 6.5753 | 240 | 2.4270 | 1.3199 | |
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| 2.1703 | 7.3973 | 270 | 2.4223 | 1.3576 | |
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| 2.1366 | 8.2192 | 300 | 2.4054 | 1.4085 | |
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| 2.123 | 9.0411 | 330 | 2.4006 | 1.4180 | |
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| 2.1331 | 9.8630 | 360 | 2.3981 | 1.3985 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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