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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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- bem |
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- robust-speech-event |
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model-index: |
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- name: wav2vec2-large-xls-r-300m-bemba-fds |
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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-xls-r-300m-bemba-fds |
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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 [BembaSpeech](https://github.com/csikasote/BembaSpeech) dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3594 |
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- Wer: 0.3838 |
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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: 0.0003 |
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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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- num_epochs: 30 |
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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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| 2.9961 | 0.67 | 500 | 0.5157 | 0.7133 | |
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| 0.5903 | 1.34 | 1000 | 0.3663 | 0.4989 | |
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| 0.4804 | 2.02 | 1500 | 0.3547 | 0.4653 | |
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| 0.4146 | 2.69 | 2000 | 0.3274 | 0.4345 | |
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| 0.3792 | 3.36 | 2500 | 0.3586 | 0.4640 | |
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| 0.3509 | 4.03 | 3000 | 0.3360 | 0.4316 | |
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| 0.3114 | 4.7 | 3500 | 0.3382 | 0.4303 | |
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| 0.2935 | 5.38 | 4000 | 0.3263 | 0.4091 | |
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| 0.2723 | 6.05 | 4500 | 0.3348 | 0.4175 | |
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| 0.2502 | 6.72 | 5000 | 0.3317 | 0.4147 | |
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| 0.2334 | 7.39 | 5500 | 0.3542 | 0.4030 | |
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| 0.2287 | 8.06 | 6000 | 0.3594 | 0.4067 | |
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### Framework versions |
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- Transformers 4.11.3 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 1.13.3 |
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- Tokenizers 0.10.3 |
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