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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-xls-r-300m |
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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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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-large-xls-r-300m-tr-colab |
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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 |
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type: common_voice |
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config: tr |
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split: test |
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args: tr |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.3005821672964968 |
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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-tr-colab |
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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 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3889 |
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- Wer: 0.3006 |
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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: 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: 30 |
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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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| 3.8274 | 3.67 | 400 | 0.6752 | 0.6946 | |
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| 0.4002 | 7.34 | 800 | 0.4440 | 0.5183 | |
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| 0.1961 | 11.01 | 1200 | 0.4133 | 0.4052 | |
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| 0.1285 | 14.68 | 1600 | 0.4249 | 0.3737 | |
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| 0.0966 | 18.35 | 2000 | 0.4019 | 0.3606 | |
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| 0.0789 | 22.02 | 2400 | 0.4019 | 0.3316 | |
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| 0.0599 | 25.69 | 2800 | 0.3996 | 0.3078 | |
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| 0.047 | 29.36 | 3200 | 0.3889 | 0.3006 | |
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### Framework versions |
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- Transformers 4.33.3 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.13.3 |
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