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---
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: 0.6215063253898205
---
<!-- 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: 80.4388
- Accuracy: 0.6215
- Test Accuracy: 0.6215
- Df Accuracy: 0.1346
- Unlearn Overall Accuracy: 0.7435
- Unlearn Time: 640.7721
## 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: 8
- 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: 5
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Overall Accuracy | Unlearn Overall Accuracy | Time |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:----------------:|:------------------------:|:----:|
| No log | 1.0 | 189 | 7.6645 | 0.1343 | 0.7433 | 0.7433 | -1 |
| No log | 2.0 | 378 | 30.0267 | 0.2179 | 0.7179 | 0.7179 | -1 |
| No log | 3.0 | 567 | 58.5008 | 0.1343 | 0.7433 | 0.7433 | -1 |
| No log | 4.0 | 756 | 74.2509 | 0.1432 | 0.7403 | 0.7403 | -1 |
| No log | 5.0 | 945 | 80.4388 | 0.1346 | 0.7435 | 0.7435 | -1 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2
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