Instructions to use mazesmazes/tiny-audio-next-plus with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use mazesmazes/tiny-audio-next-plus with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="mazesmazes/tiny-audio-next-plus", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("mazesmazes/tiny-audio-next-plus", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
Model save
Browse files
README.md
CHANGED
|
@@ -1,199 +1,99 @@
|
|
| 1 |
---
|
| 2 |
library_name: transformers
|
| 3 |
-
tags:
|
|
|
|
|
|
|
|
|
|
|
|
|
| 4 |
---
|
| 5 |
|
| 6 |
-
|
| 7 |
-
|
| 8 |
-
|
| 9 |
-
|
| 10 |
-
|
| 11 |
-
|
| 12 |
-
|
| 13 |
-
|
| 14 |
-
|
| 15 |
-
|
| 16 |
-
|
| 17 |
-
|
| 18 |
-
|
| 19 |
-
|
| 20 |
-
|
| 21 |
-
|
| 22 |
-
|
| 23 |
-
|
| 24 |
-
|
| 25 |
-
|
| 26 |
-
|
| 27 |
-
|
| 28 |
-
|
| 29 |
-
|
| 30 |
-
|
| 31 |
-
|
| 32 |
-
-
|
| 33 |
-
-
|
| 34 |
-
-
|
| 35 |
-
|
| 36 |
-
|
| 37 |
-
|
| 38 |
-
|
| 39 |
-
|
| 40 |
-
|
| 41 |
-
|
| 42 |
-
|
| 43 |
-
|
| 44 |
-
|
| 45 |
-
|
| 46 |
-
|
| 47 |
-
|
| 48 |
-
|
| 49 |
-
|
| 50 |
-
|
| 51 |
-
|
| 52 |
-
|
| 53 |
-
|
| 54 |
-
|
| 55 |
-
|
| 56 |
-
|
| 57 |
-
|
| 58 |
-
|
| 59 |
-
|
| 60 |
-
|
| 61 |
-
|
| 62 |
-
|
| 63 |
-
|
| 64 |
-
|
| 65 |
-
|
| 66 |
-
|
| 67 |
-
|
| 68 |
-
|
| 69 |
-
|
| 70 |
-
|
| 71 |
-
|
| 72 |
-
|
| 73 |
-
|
| 74 |
-
|
| 75 |
-
|
| 76 |
-
|
| 77 |
-
|
| 78 |
-
|
| 79 |
-
|
| 80 |
-
|
| 81 |
-
|
| 82 |
-
|
| 83 |
-
|
| 84 |
-
|
| 85 |
-
|
| 86 |
-
|
| 87 |
-
|
| 88 |
-
|
| 89 |
-
|
| 90 |
-
|
| 91 |
-
|
| 92 |
-
|
| 93 |
-
|
| 94 |
-
|
| 95 |
-
-
|
| 96 |
-
|
| 97 |
-
#### Speeds, Sizes, Times [optional]
|
| 98 |
-
|
| 99 |
-
<!-- This section provides information about throughput, start/end time, checkpoint size if relevant, etc. -->
|
| 100 |
-
|
| 101 |
-
[More Information Needed]
|
| 102 |
-
|
| 103 |
-
## Evaluation
|
| 104 |
-
|
| 105 |
-
<!-- This section describes the evaluation protocols and provides the results. -->
|
| 106 |
-
|
| 107 |
-
### Testing Data, Factors & Metrics
|
| 108 |
-
|
| 109 |
-
#### Testing Data
|
| 110 |
-
|
| 111 |
-
<!-- This should link to a Dataset Card if possible. -->
|
| 112 |
-
|
| 113 |
-
[More Information Needed]
|
| 114 |
-
|
| 115 |
-
#### Factors
|
| 116 |
-
|
| 117 |
-
<!-- These are the things the evaluation is disaggregating by, e.g., subpopulations or domains. -->
|
| 118 |
-
|
| 119 |
-
[More Information Needed]
|
| 120 |
-
|
| 121 |
-
#### Metrics
|
| 122 |
-
|
| 123 |
-
<!-- These are the evaluation metrics being used, ideally with a description of why. -->
|
| 124 |
-
|
| 125 |
-
[More Information Needed]
|
| 126 |
-
|
| 127 |
-
### Results
|
| 128 |
-
|
| 129 |
-
[More Information Needed]
|
| 130 |
-
|
| 131 |
-
#### Summary
|
| 132 |
-
|
| 133 |
-
|
| 134 |
-
|
| 135 |
-
## Model Examination [optional]
|
| 136 |
-
|
| 137 |
-
<!-- Relevant interpretability work for the model goes here -->
|
| 138 |
-
|
| 139 |
-
[More Information Needed]
|
| 140 |
-
|
| 141 |
-
## Environmental Impact
|
| 142 |
-
|
| 143 |
-
<!-- Total emissions (in grams of CO2eq) and additional considerations, such as electricity usage, go here. Edit the suggested text below accordingly -->
|
| 144 |
-
|
| 145 |
-
Carbon emissions can be estimated using the [Machine Learning Impact calculator](https://mlco2.github.io/impact#compute) presented in [Lacoste et al. (2019)](https://arxiv.org/abs/1910.09700).
|
| 146 |
-
|
| 147 |
-
- **Hardware Type:** [More Information Needed]
|
| 148 |
-
- **Hours used:** [More Information Needed]
|
| 149 |
-
- **Cloud Provider:** [More Information Needed]
|
| 150 |
-
- **Compute Region:** [More Information Needed]
|
| 151 |
-
- **Carbon Emitted:** [More Information Needed]
|
| 152 |
-
|
| 153 |
-
## Technical Specifications [optional]
|
| 154 |
-
|
| 155 |
-
### Model Architecture and Objective
|
| 156 |
-
|
| 157 |
-
[More Information Needed]
|
| 158 |
-
|
| 159 |
-
### Compute Infrastructure
|
| 160 |
-
|
| 161 |
-
[More Information Needed]
|
| 162 |
-
|
| 163 |
-
#### Hardware
|
| 164 |
-
|
| 165 |
-
[More Information Needed]
|
| 166 |
-
|
| 167 |
-
#### Software
|
| 168 |
-
|
| 169 |
-
[More Information Needed]
|
| 170 |
-
|
| 171 |
-
## Citation [optional]
|
| 172 |
-
|
| 173 |
-
<!-- If there is a paper or blog post introducing the model, the APA and Bibtex information for that should go in this section. -->
|
| 174 |
-
|
| 175 |
-
**BibTeX:**
|
| 176 |
-
|
| 177 |
-
[More Information Needed]
|
| 178 |
-
|
| 179 |
-
**APA:**
|
| 180 |
-
|
| 181 |
-
[More Information Needed]
|
| 182 |
-
|
| 183 |
-
## Glossary [optional]
|
| 184 |
-
|
| 185 |
-
<!-- If relevant, include terms and calculations in this section that can help readers understand the model or model card. -->
|
| 186 |
-
|
| 187 |
-
[More Information Needed]
|
| 188 |
-
|
| 189 |
-
## More Information [optional]
|
| 190 |
-
|
| 191 |
-
[More Information Needed]
|
| 192 |
-
|
| 193 |
-
## Model Card Authors [optional]
|
| 194 |
-
|
| 195 |
-
[More Information Needed]
|
| 196 |
-
|
| 197 |
-
## Model Card Contact
|
| 198 |
-
|
| 199 |
-
[More Information Needed]
|
|
|
|
| 1 |
---
|
| 2 |
library_name: transformers
|
| 3 |
+
tags:
|
| 4 |
+
- generated_from_trainer
|
| 5 |
+
model-index:
|
| 6 |
+
- name: tiny-audio-next-plus
|
| 7 |
+
results: []
|
| 8 |
---
|
| 9 |
|
| 10 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 11 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 12 |
+
|
| 13 |
+
# tiny-audio-next-plus
|
| 14 |
+
|
| 15 |
+
This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
|
| 16 |
+
It achieves the following results on the evaluation set:
|
| 17 |
+
- Loss: 0.3325
|
| 18 |
+
|
| 19 |
+
## Model description
|
| 20 |
+
|
| 21 |
+
More information needed
|
| 22 |
+
|
| 23 |
+
## Intended uses & limitations
|
| 24 |
+
|
| 25 |
+
More information needed
|
| 26 |
+
|
| 27 |
+
## Training and evaluation data
|
| 28 |
+
|
| 29 |
+
More information needed
|
| 30 |
+
|
| 31 |
+
## Training procedure
|
| 32 |
+
|
| 33 |
+
### Training hyperparameters
|
| 34 |
+
|
| 35 |
+
The following hyperparameters were used during training:
|
| 36 |
+
- learning_rate: 0.001
|
| 37 |
+
- train_batch_size: 50
|
| 38 |
+
- eval_batch_size: 50
|
| 39 |
+
- seed: 43
|
| 40 |
+
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-06 and optimizer_args=No additional optimizer arguments
|
| 41 |
+
- lr_scheduler_type: cosine_with_min_lr
|
| 42 |
+
- lr_scheduler_warmup_steps: 5000
|
| 43 |
+
- num_epochs: 2
|
| 44 |
+
|
| 45 |
+
### Training results
|
| 46 |
+
|
| 47 |
+
| Training Loss | Epoch | Step | Validation Loss |
|
| 48 |
+
|:-------------:|:------:|:-----:|:---------------:|
|
| 49 |
+
| 0.3891 | 0.0470 | 2000 | 0.4868 |
|
| 50 |
+
| 0.3933 | 0.0939 | 4000 | 0.4988 |
|
| 51 |
+
| 0.3770 | 0.1409 | 6000 | 0.4885 |
|
| 52 |
+
| 0.3654 | 0.1879 | 8000 | 0.4802 |
|
| 53 |
+
| 0.3559 | 0.2348 | 10000 | 0.4621 |
|
| 54 |
+
| 0.3294 | 0.2818 | 12000 | 0.4519 |
|
| 55 |
+
| 0.3267 | 0.3287 | 14000 | 0.4353 |
|
| 56 |
+
| 0.3255 | 0.3757 | 16000 | 0.4314 |
|
| 57 |
+
| 0.3155 | 0.4227 | 18000 | 0.4185 |
|
| 58 |
+
| 0.3009 | 0.4696 | 20000 | 0.4137 |
|
| 59 |
+
| 0.2966 | 0.5166 | 22000 | 0.4031 |
|
| 60 |
+
| 0.3016 | 0.5636 | 24000 | 0.3930 |
|
| 61 |
+
| 0.2919 | 0.6105 | 26000 | 0.3963 |
|
| 62 |
+
| 0.2842 | 0.6575 | 28000 | 0.3966 |
|
| 63 |
+
| 0.2757 | 0.7045 | 30000 | 0.3915 |
|
| 64 |
+
| 0.2811 | 0.7514 | 32000 | 0.3801 |
|
| 65 |
+
| 0.2803 | 0.7984 | 34000 | 0.3814 |
|
| 66 |
+
| 0.2594 | 0.8453 | 36000 | 0.3727 |
|
| 67 |
+
| 0.2460 | 0.8923 | 38000 | 0.3671 |
|
| 68 |
+
| 0.2588 | 0.9393 | 40000 | 0.3607 |
|
| 69 |
+
| 0.2664 | 0.9862 | 42000 | 0.3618 |
|
| 70 |
+
| 0.2111 | 1.0332 | 44000 | 0.3581 |
|
| 71 |
+
| 0.2046 | 1.0802 | 46000 | 0.3639 |
|
| 72 |
+
| 0.2081 | 1.1271 | 48000 | 0.3586 |
|
| 73 |
+
| 0.2014 | 1.1741 | 50000 | 0.3615 |
|
| 74 |
+
| 0.2073 | 1.2211 | 52000 | 0.3573 |
|
| 75 |
+
| 0.2003 | 1.2680 | 54000 | 0.3545 |
|
| 76 |
+
| 0.2013 | 1.3150 | 56000 | 0.3547 |
|
| 77 |
+
| 0.1936 | 1.3619 | 58000 | 0.3559 |
|
| 78 |
+
| 0.1921 | 1.4089 | 60000 | 0.3469 |
|
| 79 |
+
| 0.1774 | 1.4559 | 62000 | 0.3473 |
|
| 80 |
+
| 0.2008 | 1.5028 | 64000 | 0.3444 |
|
| 81 |
+
| 0.1949 | 1.5498 | 66000 | 0.3459 |
|
| 82 |
+
| 0.1883 | 1.5968 | 68000 | 0.3462 |
|
| 83 |
+
| 0.1728 | 1.6437 | 70000 | 0.3425 |
|
| 84 |
+
| 0.1785 | 1.6907 | 72000 | 0.3413 |
|
| 85 |
+
| 0.1816 | 1.7377 | 74000 | 0.3396 |
|
| 86 |
+
| 0.1796 | 1.7846 | 76000 | 0.3359 |
|
| 87 |
+
| 0.1791 | 1.8316 | 78000 | 0.3358 |
|
| 88 |
+
| 0.2006 | 1.8786 | 80000 | 0.3367 |
|
| 89 |
+
| 0.1800 | 1.9255 | 82000 | 0.3317 |
|
| 90 |
+
| 0.1833 | 1.9725 | 84000 | 0.3344 |
|
| 91 |
+
| 0.1848 | 2.0 | 85172 | 0.3325 |
|
| 92 |
+
|
| 93 |
+
|
| 94 |
+
### Framework versions
|
| 95 |
+
|
| 96 |
+
- Transformers 5.7.0
|
| 97 |
+
- Pytorch 2.8.0+cu128
|
| 98 |
+
- Datasets 3.6.0
|
| 99 |
+
- Tokenizers 0.22.2
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|