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---
license: apache-2.0
base_model: facebook/wav2vec2-base-960h
tags:
- generated_from_trainer
datasets:
- speech_commands
metrics:
- accuracy
model-index:
- name: wav2vec2-base-960h-speech-commands
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: speech_commands
type: speech_commands
config: v0.02
split: None
args: v0.02
metrics:
- name: Accuracy
type: accuracy
value: 0.8066546762589928
---
<!-- 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. -->
# wav2vec2-base-960h-speech-commands
This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co./facebook/wav2vec2-base-960h) on the speech_commands dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1612
- Accuracy: 0.8067
## 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: 48
- eval_batch_size: 48
- 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: 20
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.745 | 1.0 | 824 | 1.9237 | 0.7648 |
| 0.5664 | 2.0 | 1648 | 1.1424 | 0.7878 |
| 0.4337 | 3.0 | 2472 | 1.1234 | 0.8013 |
| 0.3346 | 4.0 | 3296 | 1.1040 | 0.8035 |
| 0.2683 | 5.0 | 4120 | 1.3128 | 0.7905 |
| 0.3498 | 6.0 | 4944 | 1.2172 | 0.7972 |
| 0.2556 | 7.0 | 5768 | 1.1906 | 0.7986 |
| 0.226 | 8.0 | 6592 | 1.1081 | 0.8044 |
| 0.2317 | 9.0 | 7416 | 1.1068 | 0.8049 |
| 0.1144 | 10.0 | 8240 | 1.1612 | 0.8067 |
| 0.2143 | 11.0 | 9064 | 1.1577 | 0.8031 |
| 0.1668 | 12.0 | 9888 | 1.1343 | 0.8058 |
| 0.2504 | 13.0 | 10712 | 1.0583 | 0.8067 |
| 0.218 | 14.0 | 11536 | 1.0677 | 0.8026 |
| 0.1025 | 15.0 | 12360 | 1.0690 | 0.8053 |
### Framework versions
- Transformers 4.43.3
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1
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