Downloads · 30 days
3
3% of all-time downloads
wav2vec2-large-xls-r-300m-dm32
jobezking/wav2vec2-large-xls-r-300m-dm32
wav2vec2-large-xls-r-300m-dm32 is a machine learning model from jobezking. Use it for the machine learning task on the model card, and read the license before you ship it in a product. 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. --
All-time downloads
116
Public
Parameters
316M
8.9 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors1.3 GB · 100%
At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- wav2vec2
- Access
- Public
- Created
- Mar 2, 2026
- Updated
- Mar 4, 2026
- SHA
- 255ca732
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-xls-r-300m-dm32
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5927
- Accuracy: 0.75
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: 0.0001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- 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: 0.1
- num_epochs: 22
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 2.2759 | 34 | 0.6773 | 0.6042 |
| No log | 4.5517 | 68 | 0.6782 | 0.5833 |
| No log | 6.8276 | 102 | 0.6817 | 0.5833 |
| 0.7000 | 9.0690 | 136 | 0.6717 | 0.6042 |
| 0.7000 | 11.3448 | 170 | 0.6290 | 0.6667 |
| 0.7000 | 13.6207 | 204 | 0.6850 | 0.5625 |
| 0.7000 | 15.8966 | 238 | 0.5779 | 0.7292 |
| 0.6302 | 18.1379 | 272 | 0.5747 | 0.7292 |
| 0.6302 | 20.4138 | 306 | 0.5927 | 0.75 |
Framework versions
- Transformers 5.2.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Mar 2, 2026
- Updated
- Mar 4, 2026