File size: 2,288 Bytes
39e7a64 |
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/hubert-base-ls960
tags:
- audio-classification
- generated_from_trainer
datasets:
- superb
metrics:
- accuracy
model-index:
- name: superb_si_42
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: superb
type: superb
config: si
split: validation
args: si
metrics:
- name: Accuracy
type: accuracy
value: 0.15773464658169178
---
<!-- 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_si_42
This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on the superb dataset.
It achieves the following results on the evaluation set:
- Loss: 3.9981
- Accuracy: 0.1577
## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 6.2927 | 1.0 | 4324 | 6.5321 | 0.0049 |
| 5.6909 | 2.0 | 8648 | 6.0103 | 0.0088 |
| 5.3829 | 3.0 | 12972 | 5.5309 | 0.0235 |
| 4.9995 | 4.0 | 17296 | 5.1894 | 0.0379 |
| 4.7591 | 5.0 | 21620 | 4.8644 | 0.0620 |
| 4.5243 | 6.0 | 25944 | 4.6042 | 0.0859 |
| 4.2486 | 7.0 | 30268 | 4.3497 | 0.1173 |
| 4.0813 | 8.0 | 34592 | 4.1215 | 0.1405 |
| 3.9317 | 9.0 | 38916 | 4.0431 | 0.1508 |
| 3.8568 | 10.0 | 43240 | 3.9981 | 0.1577 |
### Framework versions
- Transformers 4.40.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
|