Downloads · 30 days
6
3% of all-time downloads
my_awesome_asr_mind_model
chasedreaminf/my_awesome_asr_mind_model
my_awesome_asr_mind_model is a automatic speech recognition model from chasedreaminf. 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
227
Public
Parameters
94.4M
2.6 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors378 MB · 100%
At a glance
- Task
- Automatic Speech Recognition
- Library
- transformers
- License
- apache-2.0
- Model type
- wav2vec2
- Access
- Public
- Created
- Jan 24, 2024
- Updated
- Feb 3, 2024
- SHA
- 337b3157
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. -->
my_awesome_asr_mind_model
This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.8925
- Wer: 0.4558
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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 4.5119 | 1.77 | 100 | 4.1083 | 1.0 |
| 3.287 | 3.54 | 200 | 3.2437 | 1.0 |
| 3.1513 | 5.31 | 300 | 3.1230 | 1.0 |
| 3.0487 | 7.08 | 400 | 3.0786 | 1.0 |
| 3.0241 | 8.85 | 500 | 3.0934 | 1.0 |
| 2.9968 | 10.62 | 600 | 2.9948 | 1.0 |
| 2.9601 | 12.39 | 700 | 2.9549 | 1.0 |
| 2.9061 | 14.16 | 800 | 2.8990 | 1.0 |
| 2.3543 | 15.93 | 900 | 2.2582 | 0.9272 |
| 1.3794 | 17.7 | 1000 | 1.7532 | 0.8179 |
| 0.8947 | 19.47 | 1100 | 1.2148 | 0.6710 |
| 0.5989 | 21.24 | 1200 | 1.3229 | 0.5579 |
| 0.5861 | 23.01 | 1300 | 1.4233 | 0.5267 |
| 0.4311 | 24.78 | 1400 | 1.5458 | 0.5104 |
| 0.3286 | 26.55 | 1500 | 1.6509 | 0.5039 |
| 0.2765 | 28.32 | 1600 | 1.6818 | 0.4948 |
| 0.2541 | 30.09 | 1700 | 1.7650 | 0.4629 |
| 0.2151 | 31.86 | 1800 | 1.7185 | 0.4460 |
| 0.1959 | 33.63 | 1900 | 1.9164 | 0.4577 |
| 0.1909 | 35.4 | 2000 | 1.8925 | 0.4558 |
Framework versions
- Transformers 4.37.1
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
- Task
- Automatic Speech Recognition
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- Jan 24, 2024
- Updated
- Feb 3, 2024