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wav2vec2-large-xls-r-300m-euskera2.2-colab
KatMarie/wav2vec2-large-xls-r-300m-euskera2.2-colab
wav2vec2-large-xls-r-300m-euskera2.2-colab is a automatic speech recognition model from KatMarie. Use it when you need speech turned into text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- apache-2.0
- Model type
- wav2vec2
- Access
- Public
- Created
- Aug 29, 2023
- Updated
- Aug 31, 2023
- SHA
- dde025a9
Base models
Datasets
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
wav2vec2-large-xls-r-300m-euskera2.2-colab
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice dataset. It achieves the following results on the evaluation set:
- Loss: 0.2252
- Wer: 0.3388
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 4.3751 | 0.64 | 300 | 2.7513 | 0.9999 |
| 0.7411 | 1.28 | 600 | 0.3982 | 0.5537 |
| 0.265 | 1.92 | 900 | 0.2748 | 0.4088 |
| 0.1513 | 2.56 | 1200 | 0.2252 | 0.3388 |
Framework versions
- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Aug 29, 2023
- Updated
- Aug 31, 2023