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wav2vec2-large-mms-1b-livvi-karelian-CodeSwitching
Mihaj/wav2vec2-large-mms-1b-livvi-karelian-CodeSwitching
wav2vec2-large-mms-1b-livvi-karelian-CodeSwitching is a automatic speech recognition model from Mihaj. Use it when you need speech turned into text. It is set up for transformers. The card lists the license as cc-by-nc-4.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- cc-by-nc-4.0
- Model type
- wav2vec2
- Access
- Public
- Created
- May 27, 2024
- Updated
- May 30, 2024
- SHA
- 1a0fd065
Base models
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-mms-1b-livvi-karelian-CodeSwitching
This model is a fine-tuned version of facebook/mms-1b-all on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3113
- Wer: 0.4087
- Cer: 0.0910
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: 0.0005
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 10000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 1.4219 | 4.5351 | 500 | 0.4570 | 0.5677 | 0.1335 |
| 0.5951 | 9.0703 | 1000 | 0.4008 | 0.5142 | 0.1186 |
| 0.5314 | 13.6054 | 1500 | 0.3725 | 0.4942 | 0.1126 |
| 0.4916 | 18.1406 | 2000 | 0.3626 | 0.4692 | 0.1067 |
| 0.4563 | 22.6757 | 2500 | 0.3465 | 0.4540 | 0.1035 |
| 0.4331 | 27.2109 | 3000 | 0.3310 | 0.4455 | 0.1010 |
| 0.4129 | 31.7460 | 3500 | 0.3283 | 0.4516 | 0.1019 |
| 0.394 | 36.2812 | 4000 | 0.3289 | 0.4482 | 0.0994 |
| 0.3715 | 40.8163 | 4500 | 0.3203 | 0.4374 | 0.0985 |
| 0.3646 | 45.3515 | 5000 | 0.3109 | 0.4327 | 0.0966 |
| 0.3508 | 49.8866 | 5500 | 0.3136 | 0.4276 | 0.0958 |
| 0.3376 | 54.4218 | 6000 | 0.3198 | 0.4246 | 0.0950 |
| 0.3283 | 58.9569 | 6500 | 0.3203 | 0.4232 | 0.0943 |
| 0.3222 | 63.4921 | 7000 | 0.3126 | 0.4134 | 0.0932 |
| 0.3104 | 68.0272 | 7500 | 0.3140 | 0.4168 | 0.0933 |
| 0.3026 | 72.5624 | 8000 | 0.3136 | 0.4110 | 0.0920 |
| 0.3003 | 77.0975 | 8500 | 0.3137 | 0.4175 | 0.0926 |
| 0.2896 | 81.6327 | 9000 | 0.3150 | 0.4107 | 0.0912 |
| 0.2885 | 86.1678 | 9500 | 0.3110 | 0.4090 | 0.0914 |
| 0.2869 | 90.7029 | 10000 | 0.3113 | 0.4087 | 0.0910 |
Framework versions
- Transformers 4.41.0.dev0
- Pytorch 2.2.2
- Datasets 2.19.0
- Tokenizers 0.19.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- cc-by-nc-4.0
- Created
- May 27, 2024
- Updated
- May 30, 2024