Downloads · 30 days
8
4% of all-time downloads
wav2vec2-large-xls-r-300m-gn
vishwa27/wav2vec2-large-xls-r-300m-gn
wav2vec2-large-xls-r-300m-gn is a automatic speech recognition model from vishwa27. 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. --
All-time downloads
179
Public
Parameters
315M
11.4 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors1.3 GB · 100%
At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- apache-2.0
- Model type
- wav2vec2
- Access
- Public
- Created
- Nov 2, 2023
- Updated
- Nov 2, 2023
- SHA
- 597af76c
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-gn
This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53-spanish on the common_voice_13_0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3713
- Wer: 0.3431
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: 30
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.7177 | 3.62 | 400 | 0.3649 | 0.5816 |
| 0.2738 | 7.24 | 800 | 0.4029 | 0.5024 |
| 0.1768 | 10.86 | 1200 | 0.3779 | 0.4285 |
| 0.1128 | 14.48 | 1600 | 0.3929 | 0.4205 |
| 0.0842 | 18.1 | 2000 | 0.3683 | 0.3916 |
| 0.0616 | 21.72 | 2400 | 0.3943 | 0.3675 |
| 0.0461 | 25.34 | 2800 | 0.4127 | 0.3571 |
| 0.0368 | 28.96 | 3200 | 0.3713 | 0.3431 |
Framework versions
- Transformers 4.35.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Nov 2, 2023
- Updated
- Nov 2, 2023