Downloads · 30 days
7
14% of all-time downloads
outputs_finetune
SergeyAdamyan/outputs_finetune
outputs_finetune is a automatic speech recognition model from SergeyAdamyan. 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
51
Public
Parameters
581M
25.5 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors2.3 GB · 100%
At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- Model type
- wav2vec2-bert
- Access
- Public
- Created
- Nov 20, 2025
- Updated
- Nov 20, 2025
- SHA
- 5b891fd1
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. -->
outputs_finetune
This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.2984
- Wer: 0.3263
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: 5e-06
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use 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: 200
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.4228 | 0.4235 | 500 | 0.3795 | 0.3611 |
| 0.4087 | 0.8471 | 1000 | 0.3629 | 0.3577 |
| 0.4571 | 1.2702 | 1500 | 0.3507 | 0.3522 |
| 0.436 | 1.6938 | 2000 | 0.3376 | 0.3520 |
| 0.312 | 2.1169 | 2500 | 0.3319 | 0.3435 |
| 0.2703 | 2.5404 | 3000 | 0.3184 | 0.3401 |
| 0.3071 | 2.9640 | 3500 | 0.3164 | 0.3380 |
| 0.3906 | 3.3871 | 4000 | 0.3122 | 0.3368 |
| 0.3769 | 3.8107 | 4500 | 0.3046 | 0.3295 |
| 0.3311 | 4.2338 | 5000 | 0.2996 | 0.3282 |
| 0.3525 | 4.6573 | 5500 | 0.2984 | 0.3263 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.9.1+cu128
- Datasets 4.4.1
- Tokenizers 0.22.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2-bert
- Created
- Nov 20, 2025
- Updated
- Nov 20, 2025