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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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- el |
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- robust-speech-event |
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- model_for_talk |
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- hf-asr-leaderboard |
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datasets: |
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- mozilla-foundation/common_voice_7_0 |
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model-index: |
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- name: XLS-R-300M - Greek |
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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 7 |
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type: mozilla-foundation/common_voice_7_0 |
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args: el |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 102.23963133640552 |
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- name: Test CER |
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type: cer |
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value: 146.28 |
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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: Robust Speech Event - Dev Data |
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type: speech-recognition-community-v2/dev_data |
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args: el |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 99.92 |
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- name: Test CER |
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type: cer |
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value: 132.38 |
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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: 0.6592 |
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- Wer: 0.4564 |
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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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| 3.0928 | 4.42 | 500 | 3.0804 | 1.0073 | |
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| 1.4505 | 8.85 | 1000 | 0.9038 | 0.7330 | |
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| 1.2207 | 13.27 | 1500 | 0.7375 | 0.6045 | |
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| 1.0695 | 17.7 | 2000 | 0.7119 | 0.5441 | |
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| 1.0104 | 22.12 | 2500 | 0.6069 | 0.5296 | |
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| 0.9299 | 26.55 | 3000 | 0.6168 | 0.5206 | |
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| 0.8588 | 30.97 | 3500 | 0.6382 | 0.5171 | |
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| 0.7942 | 35.4 | 4000 | 0.6048 | 0.4988 | |
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| 0.7808 | 39.82 | 4500 | 0.6730 | 0.5084 | |
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| 0.743 | 44.25 | 5000 | 0.6749 | 0.5012 | |
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| 0.6652 | 48.67 | 5500 | 0.6491 | 0.4735 | |
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| 0.6386 | 53.1 | 6000 | 0.6928 | 0.4954 | |
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| 0.5945 | 57.52 | 6500 | 0.6359 | 0.4798 | |
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| 0.5561 | 61.95 | 7000 | 0.6409 | 0.4799 | |
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| 0.5464 | 66.37 | 7500 | 0.6452 | 0.4691 | |
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| 0.5119 | 70.8 | 8000 | 0.6376 | 0.4657 | |
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| 0.474 | 75.22 | 8500 | 0.6541 | 0.4700 | |
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| 0.45 | 79.65 | 9000 | 0.6374 | 0.4571 | |
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| 0.4315 | 84.07 | 9500 | 0.6568 | 0.4625 | |
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| 0.3967 | 88.5 | 10000 | 0.6636 | 0.4605 | |
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| 0.3937 | 92.92 | 10500 | 0.6537 | 0.4597 | |
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| 0.3788 | 97.35 | 11000 | 0.6614 | 0.4589 | |
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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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