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wav2vec2-large-mms-1b-aft-el-CY
robertp408/wav2vec2-large-mms-1b-aft-el-CY
wav2vec2-large-mms-1b-aft-el-CY is a automatic speech recognition model from robertp408. 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
- Sep 28, 2025
- Updated
- Oct 7, 2025
- SHA
- 67fd8330
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-mms-1b-aft-el-CY
This model is a fine-tuned version of facebook/mms-1b-all on the audiofolder dataset. It achieves the following results on the evaluation set:
- Loss: 0.6250
- Wer: 0.4330
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: 0.001
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 6.573 | 0.2584 | 100 | 1.0665 | 0.6766 |
| 0.9412 | 0.5168 | 200 | 0.8605 | 0.5970 |
| 0.7877 | 0.7752 | 300 | 0.7948 | 0.5750 |
| 1.0771 | 1.0336 | 400 | 0.7438 | 0.5479 |
| 0.718 | 1.2920 | 500 | 0.7305 | 0.5346 |
| 0.6581 | 1.5504 | 600 | 0.7471 | 0.5057 |
| 0.9717 | 1.8088 | 700 | 0.7074 | 0.4965 |
| 0.6783 | 2.0672 | 800 | 0.6970 | 0.5007 |
| 0.6062 | 2.3256 | 900 | 0.6747 | 0.4731 |
| 0.8629 | 2.5840 | 1000 | 0.6719 | 0.4912 |
| 0.6127 | 2.8424 | 1100 | 0.6501 | 0.4662 |
| 0.5476 | 3.1008 | 1200 | 0.6517 | 0.4508 |
| 0.5371 | 3.3592 | 1300 | 0.6532 | 0.4826 |
| 0.5478 | 3.6176 | 1400 | 0.6404 | 0.4498 |
| 0.5208 | 3.8760 | 1500 | 0.6335 | 0.4469 |
| 0.7972 | 4.1344 | 1600 | 0.6376 | 0.4379 |
| 0.4907 | 4.3928 | 1700 | 0.6365 | 0.4362 |
| 0.4927 | 4.6512 | 1800 | 0.6320 | 0.4330 |
| 0.8188 | 4.9096 | 1900 | 0.6250 | 0.4330 |
Framework versions
- Transformers 4.57.0
- Pytorch 2.8.0+cu128
- Datasets 4.1.1
- Tokenizers 0.22.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- cc-by-nc-4.0
- Created
- Sep 28, 2025
- Updated
- Oct 7, 2025