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metadata
library_name: transformers
license: apache-2.0
base_model: facebook/wav2vec2-base
tags:
  - generated_from_trainer
metrics:
  - accuracy
model-index:
  - name: Wav2Vec2ForSequenceClassification-finetuned-eos_poc5_ge-di-v7-meeting-v2
    results: []

Wav2Vec2ForSequenceClassification-finetuned-eos_poc5_ge-di-v7-meeting-v2

This model is a fine-tuned version of facebook/wav2vec2-base on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.6822
  • Accuracy: 0.6114

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: 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
2.5858 0.9748 29 0.6455 0.6517
2.5709 1.9748 58 0.6422 0.6517
2.5285 2.9748 87 0.6421 0.6517
2.4906 3.9748 116 0.6335 0.6540
2.437 4.9748 145 0.6330 0.6517
2.3735 5.9748 174 0.6458 0.5972
2.1678 6.9748 203 0.6553 0.6114
2.1317 7.9748 232 0.6734 0.5900
2.0619 8.9748 261 0.6809 0.5806
1.9324 9.9748 290 0.6822 0.6114

Framework versions

  • Transformers 4.47.1
  • Pytorch 2.5.1+cu121
  • Datasets 3.2.0
  • Tokenizers 0.21.0