File size: 2,278 Bytes
2af1cff |
1 2 3 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 |
---
license: apache-2.0
base_model: facebook/wav2vec2-large
tags:
- audio-classification
- generated_from_trainer
datasets:
- superb
metrics:
- accuracy
model-index:
- name: superb_ks_42
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: superb
type: superb
config: ks
split: validation
args: ks
metrics:
- name: Accuracy
type: accuracy
value: 0.9839658723153869
---
<!-- 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. -->
# superb_ks_42
This model is a fine-tuned version of [facebook/wav2vec2-large](https://huggingface.co./facebook/wav2vec2-large) on the superb dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0856
- Accuracy: 0.9840
## 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-05
- train_batch_size: 32
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.0646 | 1.0 | 1597 | 0.1839 | 0.9625 |
| 0.3751 | 2.0 | 3194 | 0.1954 | 0.9647 |
| 0.3156 | 3.0 | 4791 | 0.1335 | 0.9744 |
| 0.257 | 4.0 | 6388 | 0.1062 | 0.9796 |
| 0.2386 | 5.0 | 7985 | 0.1029 | 0.9801 |
| 0.2085 | 6.0 | 9582 | 0.1002 | 0.9815 |
| 0.1715 | 7.0 | 11179 | 0.1031 | 0.9818 |
| 0.1575 | 8.0 | 12776 | 0.0938 | 0.9819 |
| 0.1332 | 9.0 | 14373 | 0.0896 | 0.9831 |
| 0.1288 | 10.0 | 15970 | 0.0856 | 0.9840 |
### Framework versions
- Transformers 4.40.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
|