Downloads · 30 days
12
2% of all-time downloads
wav2vec2-2-roberta-large-no-adapter-frozen-enc
speech-seq2seq/wav2vec2-2-roberta-large-no-adapter-frozen-enc
wav2vec2-2-roberta-large-no-adapter-frozen-enc is a automatic speech recognition model from speech-seq2seq. Use it when you need speech turned into text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
All-time downloads
492
Public
Repo size
34 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin3.1 GB · 100%
At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- Model type
- speech-encoder-decoder
- Access
- Public
- Created
- Mar 2, 2022
- Updated
- Feb 17, 2022
- SHA
- d4823479
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. -->
This model was trained from scratch on the librispeech_asr dataset. It achieves the following results on the evaluation set:
- Loss: 20.5959
- Wer: 1.0008
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: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 3.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 6.4796 | 0.28 | 500 | 10.7690 | 1.0 |
| 6.2294 | 0.56 | 1000 | 10.5096 | 1.0 |
| 5.7859 | 0.84 | 1500 | 13.7547 | 1.0017 |
| 6.0219 | 1.12 | 2000 | 15.4966 | 1.0007 |
| 5.9142 | 1.4 | 2500 | 18.5919 | 1.0 |
| 5.6761 | 1.68 | 3000 | 16.9601 | 1.0 |
| 5.73 | 1.96 | 3500 | 18.9857 | 1.0004 |
| 4.9793 | 2.24 | 4000 | 18.3202 | 1.0007 |
| 5.2332 | 2.52 | 4500 | 19.5416 | 1.0008 |
| 4.9792 | 2.8 | 5000 | 20.5959 | 1.0008 |
Framework versions
- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu113
- Datasets 1.18.3
- Tokenizers 0.11.0
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- speech-encoder-decoder
- Created
- Mar 2, 2022
- Updated
- Feb 17, 2022