Downloads · 30 days
17
3% of all-time downloads
xtreme_s_xlsr_300m_minds14.en-US_2
Splend1dchan/xtreme_s_xlsr_300m_minds14.en-US_2
xtreme_s_xlsr_300m_minds14.en-US_2 is a audio classification model from Splend1dchan. Use it for the audio classification 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
604
Public
Repo size
5.1 GB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin1.3 GB · 100%
At a glance
- Task
- Audio Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- wav2vec2
- Access
- Public
- Created
- May 31, 2022
- Updated
- May 31, 2022
- SHA
- 8f33d5ae
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. -->
xtreme_s_xlsr_300m_minds14.en-US_2
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the GOOGLE/XTREME_S - MINDS14.EN-US dataset. It achieves the following results on the evaluation set:
- Loss: 0.5685
- F1: 0.8747
- Accuracy: 0.8759
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: 2
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 50.0
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy |
|---|---|---|---|---|---|
| 2.6195 | 3.95 | 20 | 2.6348 | 0.0172 | 0.0816 |
| 2.5925 | 7.95 | 40 | 2.6119 | 0.0352 | 0.0851 |
| 2.1271 | 11.95 | 60 | 2.3066 | 0.1556 | 0.1986 |
| 1.2618 | 15.95 | 80 | 1.3810 | 0.6877 | 0.7128 |
| 0.5455 | 19.95 | 100 | 1.0403 | 0.6992 | 0.7270 |
| 0.2571 | 23.95 | 120 | 0.8423 | 0.8160 | 0.8121 |
| 0.3478 | 27.95 | 140 | 0.6500 | 0.8516 | 0.8440 |
| 0.0732 | 31.95 | 160 | 0.7066 | 0.8123 | 0.8156 |
| 0.1092 | 35.95 | 180 | 0.5878 | 0.8767 | 0.8759 |
| 0.0271 | 39.95 | 200 | 0.5994 | 0.8578 | 0.8617 |
| 0.4664 | 43.95 | 220 | 0.7830 | 0.8403 | 0.8440 |
| 0.0192 | 47.95 | 240 | 0.5685 | 0.8747 | 0.8759 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.11.0+cu113
- Datasets 2.1.0
- Tokenizers 0.12.1
- Task
- Audio Classification
- Library
- transformers
- Type
- wav2vec2
- License
- apache-2.0
- Created
- May 31, 2022
- Updated
- May 31, 2022