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--- |
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language: |
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- el |
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license: apache-2.0 |
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tags: |
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- automatic-speech-recognition |
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- mozilla-foundation/common_voice_7_0 |
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- generated_from_trainer |
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datasets: |
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- common_voice |
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model-index: |
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- name: wav2vec2-large-xls-r-300m-greek |
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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-greek |
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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 MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - EL dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6831 |
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- Wer: 0.4287 |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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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: 100.0 |
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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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| 3.0798 | 4.42 | 500 | 3.0010 | 1.0012 | |
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| 1.4336 | 8.85 | 1000 | 0.8481 | 0.6911 | |
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| 1.2062 | 13.27 | 1500 | 0.7312 | 0.6333 | |
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| 1.0481 | 17.7 | 2000 | 0.6850 | 0.5359 | |
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| 0.9837 | 22.12 | 2500 | 0.6337 | 0.5316 | |
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| 0.9108 | 26.55 | 3000 | 0.6258 | 0.5079 | |
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| 0.8439 | 30.97 | 3500 | 0.6301 | 0.4888 | |
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| 0.7901 | 35.4 | 4000 | 0.6245 | 0.4977 | |
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| 0.7669 | 39.82 | 4500 | 0.6164 | 0.4672 | |
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| 0.7196 | 44.25 | 5000 | 0.6039 | 0.4688 | |
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| 0.6715 | 48.67 | 5500 | 0.5900 | 0.4573 | |
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| 0.6441 | 53.1 | 6000 | 0.7002 | 0.4798 | |
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| 0.5938 | 57.52 | 6500 | 0.6249 | 0.4579 | |
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| 0.5541 | 61.95 | 7000 | 0.6184 | 0.4425 | |
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| 0.5506 | 66.37 | 7500 | 0.6963 | 0.4585 | |
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| 0.4998 | 70.8 | 8000 | 0.6778 | 0.4468 | |
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| 0.4729 | 75.22 | 8500 | 0.6383 | 0.4393 | |
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| 0.4535 | 79.65 | 9000 | 0.6593 | 0.4369 | |
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| 0.4358 | 84.07 | 9500 | 0.6914 | 0.4422 | |
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| 0.402 | 88.5 | 10000 | 0.6744 | 0.4269 | |
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| 0.3946 | 92.92 | 10500 | 0.6895 | 0.4275 | |
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| 0.3734 | 97.35 | 11000 | 0.6889 | 0.4320 | |
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### Framework versions |
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- Transformers 4.16.0.dev0 |
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- Pytorch 1.10.1+cu102 |
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- Datasets 1.17.1.dev0 |
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- Tokenizers 0.11.0 |
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