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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: test_model_dir
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: 0.035398230088495575
---
<!-- 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. -->
# test_model_dir
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: 2.7409
- Accuracy: 0.0354
## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| No log | 0.8 | 3 | 2.6436 | 0.0619 |
| No log | 1.8667 | 7 | 2.6432 | 0.0619 |
| 2.6369 | 2.9333 | 11 | 2.6476 | 0.0442 |
| 2.6369 | 4.0 | 15 | 2.6537 | 0.0708 |
| 2.6369 | 4.8 | 18 | 2.6607 | 0.0708 |
| 2.6202 | 5.8667 | 22 | 2.6715 | 0.0708 |
| 2.6202 | 6.9333 | 26 | 2.6795 | 0.0531 |
| 2.6072 | 8.0 | 30 | 2.6857 | 0.0531 |
| 2.6072 | 8.8 | 33 | 2.6839 | 0.0531 |
| 2.6072 | 9.8667 | 37 | 2.6861 | 0.0619 |
| 2.5931 | 10.9333 | 41 | 2.6896 | 0.0531 |
| 2.5931 | 12.0 | 45 | 2.6916 | 0.0442 |
| 2.5931 | 12.8 | 48 | 2.6958 | 0.0531 |
| 2.5709 | 13.8667 | 52 | 2.7015 | 0.0531 |
| 2.5709 | 14.9333 | 56 | 2.7040 | 0.0442 |
| 2.5539 | 16.0 | 60 | 2.7116 | 0.0531 |
| 2.5539 | 16.8 | 63 | 2.7192 | 0.0354 |
| 2.5539 | 17.8667 | 67 | 2.7237 | 0.0265 |
| 2.5413 | 18.9333 | 71 | 2.7218 | 0.0354 |
| 2.5413 | 20.0 | 75 | 2.7317 | 0.0265 |
| 2.5413 | 20.8 | 78 | 2.7224 | 0.0354 |
| 2.516 | 21.8667 | 82 | 2.7218 | 0.0265 |
| 2.516 | 22.9333 | 86 | 2.7273 | 0.0265 |
| 2.5084 | 24.0 | 90 | 2.7202 | 0.0442 |
| 2.5084 | 24.8 | 93 | 2.7282 | 0.0265 |
| 2.5084 | 25.8667 | 97 | 2.7359 | 0.0265 |
| 2.4734 | 26.9333 | 101 | 2.7279 | 0.0265 |
| 2.4734 | 28.0 | 105 | 2.7302 | 0.0265 |
| 2.4734 | 28.8 | 108 | 2.7367 | 0.0442 |
| 2.4653 | 29.8667 | 112 | 2.7411 | 0.0265 |
| 2.4653 | 30.9333 | 116 | 2.7394 | 0.0354 |
| 2.4439 | 32.0 | 120 | 2.7451 | 0.0354 |
| 2.4439 | 32.8 | 123 | 2.7397 | 0.0265 |
| 2.4439 | 33.8667 | 127 | 2.7356 | 0.0265 |
| 2.4314 | 34.9333 | 131 | 2.7414 | 0.0354 |
| 2.4314 | 36.0 | 135 | 2.7484 | 0.0265 |
| 2.4314 | 36.8 | 138 | 2.7482 | 0.0265 |
| 2.4165 | 37.8667 | 142 | 2.7449 | 0.0354 |
| 2.4165 | 38.9333 | 146 | 2.7414 | 0.0354 |
| 2.4129 | 40.0 | 150 | 2.7409 | 0.0354 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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