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---
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
- generated_from_trainer
datasets:
- minds14
metrics:
- accuracy
model-index:
- name: my_awesome_mind_model
results:
- task:
name: Audio Classification
type: audio-classification
dataset:
name: minds14
type: minds14
config: en-US
split: train
args: en-US
metrics:
- name: Accuracy
type: accuracy
value: 0.008849557522123894
---
<!-- 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. -->
# my_awesome_mind_model
This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the minds14 dataset.
It achieves the following results on the evaluation set:
- Loss: 2.6657
- Accuracy: 0.0088
## 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: 3e-05
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 2 | 2.6370 | 0.0973 |
| No log | 2.0 | 4 | 2.6400 | 0.0796 |
| No log | 3.0 | 6 | 2.6482 | 0.0619 |
| No log | 4.0 | 8 | 2.6541 | 0.0619 |
| 2.635 | 5.0 | 10 | 2.6597 | 0.0265 |
| 2.635 | 6.0 | 12 | 2.6623 | 0.0088 |
| 2.635 | 7.0 | 14 | 2.6633 | 0.0088 |
| 2.635 | 8.0 | 16 | 2.6648 | 0.0088 |
| 2.635 | 9.0 | 18 | 2.6653 | 0.0088 |
| 2.6268 | 10.0 | 20 | 2.6657 | 0.0088 |
### Framework versions
- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.2
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