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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_8_0 |
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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_8_0 |
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type: common_voice_8_0 |
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config: sw |
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split: test[:400] |
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args: sw |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.97 |
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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_8_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4900 |
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- Wer: 0.97 |
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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: 50 |
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- num_epochs: 5 |
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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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| 6.5497 | 0.4 | 50 | 2.9819 | 1.0 | |
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| 2.8809 | 0.8 | 100 | 2.8873 | 1.0 | |
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| 2.8416 | 1.2 | 150 | 2.8427 | 1.0 | |
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| 2.8145 | 1.6 | 200 | 2.8067 | 1.0 | |
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| 2.747 | 2.0 | 250 | 2.7092 | 1.0 | |
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| 2.1095 | 2.4 | 300 | 1.3472 | 1.0 | |
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| 0.9546 | 2.8 | 350 | 0.7708 | 0.9975 | |
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| 0.6104 | 3.2 | 400 | 0.6317 | 0.9825 | |
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| 0.4941 | 3.6 | 450 | 0.5427 | 0.97 | |
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| 0.4345 | 4.0 | 500 | 0.5314 | 0.975 | |
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| 0.3327 | 4.4 | 550 | 0.4927 | 0.9625 | |
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| 0.3099 | 4.8 | 600 | 0.4900 | 0.97 | |
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### Framework versions |
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- Transformers 4.27.4 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.11.0 |
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- Tokenizers 0.13.2 |
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